We would like to thank everyone who has responded to our request for
NEOS stories. Hopefully this page will provide an idea of the range of
applications people are attacking with NEOS. If you would like to
contribute to this page,
send us a message describing the
problems or problem types you've solved with NEOS and the solvers used
or fill out the form you
will find by clicking the Comments and Questions button at
the bottom of the page. The comments here are roughly categorized into
Education, Business & Finance, and Science & Industry sections.
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Education |
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I would like to compliment you on an excellent site - that simplifies solving semidefinite programs a lot without installing software.
I am currently trying to estimate horizontal wavenumbers using
complex
pressure measurements collected from a horizontal towed array for my PhD
dissertation at the University of Rhode Island. The idea is to estimate
the
wavenumbers and use the "wavenumber gradients" to identify the best
environments
for use in matched field processing. I am currently trying to use the
conjugate gradient
Fortran software (CGPLus).
NEOS did a great job! I am currently a graduate student. I used CGplus to
solve the conjugate gradient problem as my assignment. I really needed such
a website as a helper and reference.
I'm using NEOS for a class homework
in a graduate NLP course, just to have the students get the feel for
the possibilities of numerical solution and the great service that
NEOS provides! They'll just do a toy problem for the homework, because
they come from lots of different backgrounds, I can't teach them all
AMPL, etc. But I think it will still be instructive!
I am very pleased with your valuable AMPL service. I have been an AMPL
user for more than seven years, since I used it to run the programs of
my PhD dissertation. Now, with your Internet service, I have the
opportunity to teach my students and let them run real AMPL cases.
I will also use it in doing research.
I have used the NEOS and minlp solver running in the background to
resolve a small model on my research. It is quite great, if I have
chance I would like join into this system as well.
I'm very satisfied
with the job done... fast enough. Its for solving an assignment for
education purpose(a graduate-level course).
I have been using the mixed-integer solvers at NEOS to study the
complexity of phase retrieval, a problem encountered in several
disciplines, principally crystallography and astronomy. My NSF grant has
a budget for computer software, but not in the amount required to
purchase some of the high end optimization software at NEOS. Another
benefit provided by NEOS is that I am able to do serious number
crunching from my humble laptop.
NEOS has been a very valuable tool in the two graduate optimization courses
that I regularly teach: CS 719 Network Flows and CS 720 Integer Programming.
NEOS allows students to see a broader variety of solvers than we have
available in the Computer Sciences Department at the University of Wisconsin
-
Madison ,
and also helps to overcome a variety of time/storage limits that apply to
student jobs here. For example, the student version of AMPL packaged with the
text for CS 720 allows at most 300 constraints and 300 variables, but several
students in the course are doing course projects involving problems that are
substantially larger than those limits.
I have been teaching a course on linear and integer programming over the
past two months. Part of the course is based on projects where the
students use GAMS. Previous years, they have used the student version of
GAMS to model the project problems. This year, I have given them larger
problems where they have sent their GAMS files to NEOS and used
XPRESS-MP to solve the problems. The ability to use GAMS and not being
limited in size by the student version has been extremely useful. I find
NEOS a very useful tool for teaching this course. When the students
leave the course, they know how to build a GAMS model, and they also
know that they can solve large problems via NEOS.
Royal Institute of Technology, Stockholm
We very much appreciate the NEOS server service. We find that not only
are the solvers and the software reliable, but also that the people
maintaining and developing the codes are very helpful. The NEOS server
provides the possibility to run problems without going through the
whole process of installing a software package, paired with the
possibility to run instances on powerful machines.
At the university of Cologne we are interested in finding good bounds on the maximum cut value in sparse graphs. This problem has an application in theoretical physics and is interesting to the physicists' community. We calculate an upper bound on the exact value of the maximum cut by formulating it as a positive semidefinite program. We then add valid inequalities to tighten the relaxation. We solve the resulting problem exactly with the solvers CSDP and SDPA.
I am a PhD student at the University of Melbourne,
Australia. Recently, I have been using NEOS (solvers:PATH, DONLP2, FILTER,
MINOS) to carry out some numerical tests on a game theory model arising in
currently debated electricity restructuring.
A big thank you to NEOS staff for providing such a wonderful facility (free!).
Excellent tool! I am using it for academic research regarding
route selection in packet switched networks. I had no prior
experience in the gams language but was able to quickly hack
together a series of equations that the nlp solver was able to
give me good results with.
I would like to thank all the people who provide and maintain NEOS. At
the beginning of this summer I began a term of assisting a professor at
my university with his research. The daunting task of solving nonlinear
programming problems was put on my shoulders and I felt as though I was
in over my head. I didn't even know what nonlinear programming was and
after I discovered what it was, it became clear how enormous a task it
would be to solve the problems assigned to me. I bought Maple 6 to try
to help me, but the calculation times were huge, as well as the round
off error. Then looking for a better way, I found NEOS. With the great
abundance of help given me by the caretaker(s) of NEOS, it took a short
while to figure out how to setup the input file (I used AMPL format).
I had extremely complicated objective functions, both convex and
nonconvex, an arm load of variables, and an armload of convex,
nonconvex, equality and inequality constraints, but when I sent
off the information via the web submission form, within seconds I
received extremely accurate and consistent results. The results
were used for verifying a certain theory in my professor's research
and so accuracy was extremely important. It has been an invaluable
service to me and I truly doubt that I could have done my job to the
satisfaction of my professor. I would highly recommend NEOS to
anyone needing constrained optimization calculations done quickly
and accurately.
I am a graduate student at RPI in Troy, NY working on
non-linear polymer diffusion in confined spaces. Specifically, I am
attempting to find solutions to the modified Cahn-Hilliard equation, a
fourth order partial differential equation by techniques to minimize the
total free energy of the system. While these problems are certainly not as
complex as the large scale process optimization studies performed by other
groups, the NEOS system using the Lancelot solver has allowed me to spend
more time on experimental work that is also of interest to us since the
optimization routines are made easier to use than if I had to write them
myself. The submission process is straightforward and the availability of
the NEOS solver has allowed me to concentrate more on the physics of our
problem than the mechanics of writing optimization codes. If programs like
the IBM data visualization explorer and HDF were made as easy to use as the
optimizers from ANL, I would be ecstatic. As it is, I would encourage the
continued funding of the NEOS server at ANL and its related costs. The
service has been a great help in my progress toward a doctorate.
This is a great resource for those of us who need to demonstrate large
scale optimization to students, but who do not have enough need for this
(or funds!) to justify the purchase of a large scale optimization package.
I have been using NEOS in my nonlinear programming course every spring
semester. We use the student version of AMPL earlier in the semester, and
then I assign a larger applied problem (that is too large to be
handled by the student version), which the students are asked to model
with AMPL and then solve. In the past I have used AMPL and MINOS, but in
future semesters I plan to ask students to compare different solvers.
I have also used NEOS in assisting a non-optimization colleague of
mine to solve optimization problems relating to database design.
Hi, I've been using your server to solve complementarity models of electricity
markets (using the PATH solver and AMPL). This is academic research.
Following
is an abstract of my paper. Your site has been invaluable for me. Keep up
the good work.
This paper presents a modeling framework for analyzing competition between multiple firms that each possess a mixture of hydroelectric and thermal generation resources. Based upon the Cournot concept of oligopoly competition, the model characterizes the Cournot equilibrium conditions of a multiperiod hydro-thermal scheduling problem. Using data from the western U.S. electricity market, this framework is implemented as a mixed linear complementarity model. The results show that some firms may find it profitable to allocate considerably more hydro production to off-peak periods relative to peak periods. This strategy is a marked contrast to the optimal hydro-schedules that would arise if no firms were acting strategically. These results highlight the need to explicitly consider profit maximizing behavior when examining the impact of regulatory and environmental policies on electricity market outcomes.
I had a large very non linear problem. I used NEOS because of the AMPL
interface and the access to various solvers. Originally I had no luck
because the problem was just too large. I condensed it to one with about
11000 variables and 11000 constraints, of which about 10000 variables and
3000 constraints were nonlinear. After considerable work on the
parameters, MINOS solved many variations of the problem in about ten
minutes elapsed time each. I'd like to thank the NEOS team for their prompt
and helpful attention to some queries I had. It was great to have the
opportunity to try my problems on a number of different solvers, although
in the end, MINOS proved the most useful solver for this set.
I also found the web interface and email results made it easy to run a
large project remotely and the overall documentation is an excellent
introduction for beginners to math programming.
I used the solver CSDP via NEOS to solve several dozen semidefinite
optimization problems. These SDPs were very large, typically with over
100 variables and several thousands of constraints.
I found that the NEOS system was easy to use and quite reliable. I would certainly consider using it again in the future, as well as pointing it out to other people whose work also requires solving optimization problems.
Thank you again for setting up NEOS and for keeping it running!
We (my students and I) have been solving large semidefinite programs
(SDPs) using both SeDumi and CSDP solvers.
Both have worked excellently. We have been able to solve some very large
problems.
The problems arise from relaxations of quadratic assignment problems.
I just would like to thank you all for the neos server: it's just perfect.
I learned AMPL to use the server and this was useful for its own sake. Now
I use the server for teaching, letting the students to put hands on simple
parametric optimizations. Moreover I use the server to solve problems for
research purposes.
One of the main motivations was the ability to run very large (more than 1M
arc) network flow problems. Student accounts here have rather limited memory
allocations, and many students
had problems just storing the input data files for 1M arc problems (and the
storage for the
temporary files used by the algorithms is several times larger than the
input). I wanted
students to develop an awareness of the size of the problems that network
codes can solve,
and this would have been hard to do locally.
Additionally, I wanted students to develop a feeling for the relative speed of various network and general LP codes. NEOS provides easy access to 2 different network algorithms (both of which I teach in my course) as well as LP codes. This aspect I could have handled locally (with problems much smaller than 1M arcs), but students are generally reluctant to learn multiple interfaces, so it was very convenient to do it all via NEOS.
I think
that first we all should thank you and your colleagues
for the excellent work done with NEOS. It is a great service to the public.
I myself used it in trying out the AMPL interface for my code donlp2,
most of the other codes being installed locally here. But I know of
a colleague which uses NEOS as a teaching machinery for his nonlinear
programming courses, which could otherwise be done only by paper and
pencil due to the lack of appropriate computing resources.
I
sincerely believe "optimization on the Internet", or some people refer
to it in more general terms: "providing decision technologies over the
Internet as services", is very important and will become ever more
important in the future. For "optimization" to become a viable tool for
the "end users", they must be provided with the latest optimization
tools in a user friendly manner. NEOS relieves the end users from
"software version updating" headaches and provides very friendly and
expert guidance on their problems. I thank you for an excellent service.
I require students in my senior project course to study OTC thoroughly and solve some optimization problems making use of the NEOS services. These problems can be solved with the software available in our university, but I do this in order to provide students with some experience on use of Internet for long distance technical collaboration. I also believe resources like OTC are excellent means for continuing professional development for my students.
I am using NEOS for solving problems and examples for the classes I
teach.
Faculdade de Ciencias da Universidade de Lisboa, DEIO
Thank you very much for BonsaiG.
I used it for my master's thesis at the University of Twente, where I
scheduled iterative algorithms on multiprocessor systems.
We are using the NEOS Server to design communication networks
and system state perception of control agents for large,
distributed networks, such as the power grid, at Carnegie
Mellon University.
We are using the NEOS Server for teaching AMPL and SIF
and solving tutorial examples of nonlinear optimization.
Some students are using the NEOS Server for solving
optimization problems when writing their Diplom-thesis.
Thank you very much for managing the NEOS-Server.
Thank you so much for your works at the NEOS Server.
We are using the NEOS Server for the research of Computer Network
and solving the Network Design Problem at Osaka University in Japan.
I used NEOS for a project in a grad-level CS class at Purdue Univ this
past fall, on a network flow problem.
I had students run some
examples using NEOS in three classes since you first announced
it. No one complained :-) The only difficulties I heard
about we of the i've-never-programmed-in-Fortran variety,
and those are not your issue.
Valuable service.
We are planning to use NEOS with the (still experimental) callback
features in inverse problems arising in multiphase reactionary fluid
systems in an interdisciplinary research project at the University of
Technology Aachen.
The only computation I have done using NEOS is for unconstrained NLP (NMTR),
application to train an artificial neural network (in a project
with an engineering student). I have also presented NEOS to third
year undergraduates, to introduce them to optimization software
for NLP especially, and referred 3rd parties to the NEOS web site.
One of the main benefits of NEOS from my point of view is that
it provides a kind of one-stop-shop for people tinkering with
optimization models/methods, and is friendly enough for non-optimizers
to get along with.
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Education: Mathematics |
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I am a graduate student at the University of Pittsburgh. I am using the
Filter solver (Ampl input) to find nonlinear models for the boiling points
of alkanes. This is part of my Ph.D. thesis and a paper we are writing
that has been accepted for publication in the journal Match. We are
planning to cite the website in our paper. Dr. Mihai Anitescu is serving
on my thesis committee and directed us to your site.
I am a graduate student at the UC Davis applied math program, working
under the supervision of Dr. Naoki Saito.
It has been our pleasure to discover the power of NEOS. Currently we are
using it to solve the sparse representation problem that comes up in
neuroscience (study of the brain's representation system):
I'm a PhD Student here in Spain. I'm frequently using the NEOS solvers since
the beginning of this year, when I was told that they could be useful in
maximizing a likelihood function which has not been implemented in any
statistical package, so far.
Indeed, they are very USEFUL and help me a lot. Colleagues already consult me
in order to get to know the possibilities you offer via the internet.
For the moment, I normally use the solver SNOPT for my programs written in
AMPL, but I have to admit that, since [I am] a statistician, I need to
reinforce my knowledge about the other solvers you offer.
Summa summarum: THANK you very much!!!
I am a part-time graduate student at the University of Southern
Mississippi. My research area is in solvers for systems of algebraic
nonlinear equations. I first used MINPACK and have added LANCELOT (SIF),
LANCELOT(AMPL) and MINOS(AMPL) to the solvers included in my studies.
I have had success with LANCELOT in solving a problem that I could not
with other solvers and I also use your solvers to verify the correctness
of algorithms and other solvers that I am testing. I constantly use your
NEOS Guide and the links that your sites provide have been very useful
in all of my studies. I really appreciate the work that you have put
into making your site extremely user friendly and you sharing all of
your technical expertise.
Using the NEOS server in a class on Methods of Applied Math (Math511)
at the Math.Dept., Univ. of Tennessee.
It has been very useful. Keep up the good work!
We are using MINLP on the NEOS Server in a class on discrete design
and optimization at University of Michigan. I cannot run the class
without it!
We used the NEOS server for linear programming class at the University of
Wisconsin-Milwaukee.
I used the NEOS server as part of my course "Computational Methods
in Analysis" in both Fall 1998 and Fall 1999. There were 78 and
43 students enrolled, respectively. NEOS was used in a project to
explore and evaluate methodologies for "delivering" math software to
users. The students found that using the NEOS server was quite easy
(although there are always a few people who seem never to be able to
follow instructions) and they rated it as one of the more efficient ways
to access existing software for the optimization problem they were
assigned.
We are using the NEOS Server in a class on linear and nonlinear
programming at Ohio University.
We have used the NEOS Server in a class for deterministic optimization
in mathematical modeling at Saint Peter's College, NJ. I also use it
in an elementary finite math class as a lecture demo.
I am teaching Optimization techniques for students who want become
Diplom-Mathematiker. Our University is a University of Applied
Sciences and for our students it is important to formulate and to solve
optimization problems and it is not important to create new optimization
techniques. Therefore I give only an overview about the different
optimization techniques and then my students have to solve a wide
variety of different optimization problems; linear and nonlinear.
First the students are learning the MPS description of linear problems and then the are learning SIF. On our computers we have an old release of LANCELOT but I ask the students to solve the problems by using the NEOS server. Sending a problem to the NEOS Server, we usually received an answer in only few minutes. This is very good! I was also interested that my students use the helpful comments and suggestions on the various NEOS Web pages. The material is very good. My work is to be a moderator between the NEOS Server and my students - I think, the NEOS Server is a good [foundation] for "Computer Based Training".
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Education: O.R. & Econ. |
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I've been very impressed with the NEOS setup, so I'm taking some time to
respond to your request.
I've been using the GAMS-PATH (MCP) solver on NEOS to solve a CGE model for the South African economy, which is for my major project for a master's degree at Stellenbosch University, South Africa. The work is therefore educational.
I'm trying to incorporate economies of scale and imperfect competition into an existing South African CGE model. If it works, I'll use it to analyze economic policy issues related to trade/industrial/competition policy. The model reasonably large (43 commodities, 43 sectors, 14 households), producing a system with just under 4000 variables.
The work I'm doing would not at all be possible without NEOS, as I do not have access to fully functional GAMS software and the demo version of GAMS cannot deal with the models I need to solve. Our university wouldn't purchase a license, as there is not enough interest in such work, and my project is of course unfunded and relatively unimportant. Furthermore, the software is expensive, even when the GAMS developing country discounts are taken into account.
So, I very much appreciate being able to use NEOS to solve my models and consider it very useful for small-scale researchers such as myself. It's not quite as convenient as having GAMS on your own PC, but certainly comes close enough :)
I am a graduate student major in business. I use NEOS for a course
project in Operations Research Modeling. The problem is a linear
program with about
400 variables.
We are using the server to give our MBA-students a problem oriented
introduction
to optimization. The students build small AMPL models and let NEOS do
the computation.
It is an extremely useful service for us, because we do not have to
install
any software in our computer labs.
Thanks for the prompt reaction! I am currently developing a 100%
Java application to aid students to learn operations research. Since
the NEOS server is by far the best place on the web
where my students can submit their applications with the hope of
getting back trustable results, I am planning
to integrate the communication module.
Lately I've been using the Neos server to solve large optimization
problems formulated as semidefinite programs. Essentially, is a
combinatorial problem that models the scheduling of thermal and hydro
energy resources. This is part of my research work at the University of
Waterloo in Canada.
Because of the size of the test systems I've used, the neos server has been
quite useful.
In my microeconomics principles class, I spend some time on cost
minimization problems. Solutions to these problems are nicely
illustrated by Neos. My students and I all appreciate having Neos
available to us.
Just a comment: you are doing an excellent job and an
extraordinary service to the academic community.
I am regularly suggesting my students to use NEOS as soon
as their projects in AMPL cannot be solved with the student
edition. So they debug their AMPL models locally with AMPLPlus
(which unfortunately is no longer supported from ILOG - this
is a great damage to the operations research community) and
then they run their real-life projects thanks to NEOS.
In my laboratory we have full versions of AMPL, Cplex and
MINOS, both on a PC and on a SUN server, but the students
decidedly prefer to use NEOS from their lab or home PC.
So: many many THANKS!
I am a great fan of NEOS, and try to spread the good news
whenever I can. My most recent success was for an economics
grad student from Oxford, whose thesis was to do with
multi-person co-operation. He had a conjecture that something
(I can't claim to understand the details!) that was true for
two-person co-operation, might not be true for three or more. He
managed to formulate this as a nonlinear program, that is
if the NLP had a certain solution, his conjecture was true
(the NLP was actually the discretized version of a continuous
problem, and he wanted a fine discretization => a large NLP).
Anyway, he struggled on his own ... until I pointed him to
NEOS. Within a few hours, he had formulated his problem in AMPL,
sent it to a variety of solvers (LANCELOT, MINOS, KNITRO, LOQO
and SNOPT), interpreted the results, et voila, his conjecture was
true. I believe he has just successfully defended his thesis!
Quite apart from the fact that NEOS is extraordinarily useful for people wanting to solve real problems, it is equally wonderful for those of us who try to design new algorithms. I adore the gladiatorial aspect, put your solver up on NEOS, and let it fight, naked, against the world's finest (of course, I can't pretend that the humiliating defeats for LANCELOT don't hurt, but the experience is invaluable for our next-generation solvers).
I would like to thank the organizers of Neos for the wonderful
construction which they have undertaken and which I find extremely
efficient.
My students, all fourth year majors in OR take my course in Mathematical Programming and are using Neos to familiarize themselves with the best software available, which is invariably on your site. Thus, I would judge, but you should have machine data on this, that the favored software is Lancelot for constrained problems and CGplus, NMTR for the unconstrained case, the latter being a lot faster. The input into Lancelot which requires elemental and group function decomposition is a bit troublesome and it would be preferred to submit the functions in natural form. Probably this can be done, but we may have overlooked something.
We are also using Neos for research and for thesis development. This is very important to us, as we can use the abundant routines given to try and document how the other routines fare, as you will notice, from our user statistics. In this we have a bit of a problem in writing one input, but we expect that the only common input to most routines is AMPL so we shall have to learn it.
We will of course give due credit to Neos as the papers that we develop appear in print, since we are extremely grateful to your institutions for such a great service to science and to research. I have neither kept a research diary regarding out use of Neos, nor a didactic diary for my course, but as I find the Neos is a great idea and extremely well implemented, I would be glad on my side to do anything that might be useful to you to help the project. Thus I would be glad to keep such diaries, if you expect ask for user accounting from time to time. I have not done it, since I was not expecting such a request, but I would be glad to do it. Otherwise I feel that my information will remain rather generic, although highly appreciative of the project.
Neos is an extremely efficient computational tool and my classes of 14
students 4th year majors on OR following the course Mathematical
Programming and a graduate class use it extensively to solve problems and
thus acquire solution skills. More importantly to obtain, through
solving actual problems, the feel for the theoretical underpinnings.
I develop a rather formal course in Mathematical programming, in which the basic philosophy is that you need method to be sure that you are correct. Thus given a problem they must analyze it form a theoretical viewpoint and discover what properties the solution or solutions is likely to have. Then it is a blessing to have Neos to check that their theoretical knowledge was used to good purpose.
Thus I find the Neos project a very suitable and extremely efficient laboratory for practical optimization from a viewpoint of confirming and analyzing the robustness of the theoretical derivation by good lab work. The idea of laboratory diaries, which was suggested by your request, is I think a worthwhile idea and I will pursue in the future.
I am putting up the course as an interactive distance course on the web and the Neos server is ideal for practicing. The web course which I am developing is initially in Italian and relies on this type of laboratory work, which I can now execute through the neos email server.
I suppose that I can also allow the students to connect to my machine and use the telnet facilities to submit problems on neos. At the moment, if you notice the requests spring from my machine, because they use the Linux systems in the computing lab to telnet and exploit my machine. By the way, this also works perfectly. I will keep you posted on these developments as it is part of my research.
I have, as I said, a number of prototype software which I use for optimization. The programs allow me to estimate and optimise simultaneously and I solve the problems through a recursive programming approach which solves a quadratic subproblem at each iteration, by solving a linear complementarity subproblem, under trust region constraints. I have been developing it for a number of years and, if it is ever ready and sufficiently robust, I will present it to the Neos server so that it can be used by the MP community if they want to. With this routine I have solved innumerable problems, some extremely large, some combinatorial and so on. Again if anyone is interested I will be happy to send details of the publication of the papers.
The Neos server is very useful to gauge how traditional implementations fare against my developments. This is now what I propose to do as research in a big way on many practical problems and to launch some theses, so I expect to be using Neos very much.
Of course I am very interested in all applications and do some Supply Chain optimization, solve combinatorial problems by embedding them in continuous problems, but I think at the moment, the most fun work that I am doing is to use my simultaneous estimation and optimization routines to solve diagnostic and treatment problems in Medicine. This includes Histopathological diagnosis of colon cancer, osteoporosis detection and treatment, diabetes diagnosis and treatment and so on. These are always simultaneous estimation and optimization problems and thus require comparison with other routines, so that we can develop good theory and computational expertise.
I have used NEOS Server in various courses at University of Missouri --Rolla
and Bilkent University and encouraged graduate students to supplement their
computational work in their thesis research with various resources provided
by NEOS.
During the coming Spring semester, I will be asking students to use NEOS Server in the following two courses:
In addition, I find NEOS Server an excellent example of an Internet tool in decision sciences.
I teach
"Modeling and Optimization" in
University of Valencia (SPAIN). During the academic course, we use a GAMS
software to model and solve business problems. When the number of
variables exceeds the student version (50 binary or integer variables), we
use the NEOS Server to solve and analyze the result of our models.
I think is very interesting the possibility to use this Internet service. In my opinion this service must be continued.
I am using neos as a tool for my OR course.
The homework is to use MINLP for mixed integer programming
problems. All submissions last week are from my students!
NEOS is a very good tool for my teaching.
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Education: Engineering |
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I do appreciate your kindness in allowing me to run a number of MIP tests
with your GAMS programs and XPRESS solvers.
I am a student of the last year in Engineering & Management at COMILLAS
University in Madrid (Spain).
The purpose of my project work is to compare the feasibility, efficiency and
speed of solutions provided by existing software programs with some
genetic algorithms developed specifically for optimisation problems.
I hope to be allowed to continue using your facilities.
Thank you very much for being allowed to use your server. I am working on my PhD in industrial ecology. Much of my work is interdisciplinary, as a result of that I work with many different people who uses various types of tools. Some of my work has been on linking LP models and Environmental input output analysis with LCA. Just recently I've been running some MIP energy technology scenarios with endogenous learning. Working with different people requires often access to various tools. Through you NEOS Server I can both run my MP-models and my GAMS models. Last week my solver would not handle the size of the problems I had modeled, and thanks to your server I have been able to complete my work.
I use the NEOS server for academic purposes, as I work in
the Department of Structural Engineering, Technical
University of Milan, Italy. In my research activities I
have encountered some challenging problems of Mathematical
Programming. In detail, I am dealing with ultimate limit-state
analyses of large dams by means of a non-standard approach
("direct method"); this requires solving problems of
linear and non-linear programming. The NEOS server is an
extraordinary tool to perform parametric tests on small
models, in order to choose (also with the kind help of NEOS
operators) the best suited solver. So far I have used CONOPT,
MINOS and SNOPT, by way of the GAMS interface, for my non-linear,
non-smooth, non-convex (very cumbersome!) problems,
achieving very good results.
It was a very good experience working with the NEOS Server. I would
highly compliment the stability of the server. In the one year I used the
WWW version of the server, it probably crashed twice. I am indeed
impressed.
I had been using XPRESS-MP MILP solver to obtain power optimal equivalent inputs to logic circuits. I work in the field of Low Power VLSI Design. I formulated large circuits as ILP problems, submitted them through the WWW interface and obtained good results.
In the later part of my research, I had to solve a large number of similar problems. So I used the mailing-in option of the server. I had written a shell script to mail my problem formulation as .mod files to the server and waited for the results to arrive back, which I parsed from the inbox input and processed.
On the whole, the XPRESS-MP solver as part of the NEOS Server was indeed a pleasure to work with.
A special mention to the tech support behind the NEOS server. I received outstanding support from them.
I have been
using MINLP (AMPL version) at NEOS for my graduate class
"Discrete Design Optimization." at ME Department in the University of
Michigan. The class is offered every Fall semester (Sept -- Dec) and
enrolled by 20-30 students. Without NEOS, I would be in big trouble...
I teach a sophomore-junior class required of all civil engineers. The
title is Design and Planning of Civil Engineering Systems, and the topic is
optimization as an approach to design. The course is heavy on linear
programming, with some non-linear optimization as well. We use two
optimization engines: that contained in Excel, and Neos. Our students
have found Neos to be quite useful.
We are planning to test a number of problems related to Chemical
Engineering Process design and synthesis (which are optimisation problems)
for a postgraduate level course. The testing is with a view to incorporate
the facilities of the server for the students.
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Business & Finance |
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I have been using the NEOS site for about a month now.
It has greatly helped in the work I am doing here at General Motors.
I have been able to build and solve a prototype combinatorial auction MIP
model
using AMPL and NEOS in a fraction of the
time it would have required me to do this had I needed to requisition
a solver and install it locally. Because of this, internal GM customers
have been able to see the benefits of optimization in this business
context, and will most likely
give the go ahead for a full scale development project. This will
help GM, and will also help the solver vendor as they will probably
get a sale at the end of the project.
I have also built two prototype equilibrium models for two separate
projects and solved
them using the PATH solver. I wouldn't have even attempted going down
this road had it not been for NEOS since GM has no complementarity solvers
in-house to the best of my knowledge. As it is, I've been able to bring
this class of models to bear on these problems, and, as a result, created
a valuable solution for two different internal GM customers. These
prototype
models will also, hopefully, be eventually embedded into full blown
enterprise applications
which will, ultimately, result in a sale to the solver vendor.
Thank you again for providing such a valuable resource.
NEOS provides an interface to a variety of solvers. We use it to evaluate
various solvers/algorithms on test problems of interest.
The use is both educational and commercial.
Solvers used are MOSEK, XPRESS-MP for LP/MILP.
The application is the supply-chain optimization of global manufacturing enterprises where manufacturing activities take place across the globe around the clock.
The model is LP/MILP. Constraints are from transportation, manufacturing and warehousing capacities. Optimization is to achieve just-in-time production to meet demands on time considering the above constraints. Optimization with uncertainty is also under study.
Typical problems are very large and hence solver performance is a critical factor.
I used the MOSEK LP solver on NEOS (and lpl on my pc) to solve
problems re asset allocation. I LOVE THIS!
I am using NEOS to compare the efficiency of my code with some codes,
such as LOQO, LANCELOT, SNOPT, MINOS, .., when they solve nonlinearly
constrained nonlinear network problems. It is a researching work for me.
I am using NEOS servers for benchmark testing on one of the nonlinear
optimization solvers. This is an important part of the decision process if
we want to adopt the new optimizer. NEOS is very user-friendly, dependable
and saves a lot of research time. I would continue to use NEOS server for
this purpose.
I appreciate all the work you have done to make this project available for use to the public.
Insightful Corporation
We are using NEOS services for duty-scheduling for ground handling
activities in an regional airport environment.
At this moment, duty-scheduling is a manual process. We are investigating how much can be gained in terms of "doing the same work with less employees" by using a more advanced scheduling mechanism. In the investigation stage "LP on demand" offers a very good solution to see how much can be gained. If the results are positive, we will consider buying software tools.
We are using the XPRESS-solver.
I work at the Swiss Federal Institute of Technology in Zurich, at the
Department of Agricultural Economics.
The model I have been developing includes external costs of soil
erosion and water pollution in farmers' optimisation problem. The
model is dynamic, spatially differentiated and includes some non-linear
restrictions and binary variables.
I have been using the MINLP (AMPL input) solver. It is the best
non-linear solver that provides integer results I have found so far.
I'm writing a business app with an optimization sub-problem.
I've formulated the optimization sub-problem as a binary LP.
On my 192MB ram PC, lp_solve handles up to 10,000 variables.
I'm using NEOS to try out other solvers.
I am trying to fit a nonlinear model that estimates "Value at Risk"
of mexican financial institutions based on their assets, liabilities
and mean duration of both.
We are using the NEOS server for making an optimal duty-schedule for
employees involved in ground-handling activities in a Airport environment.
For investigating the feasibility of optimization techniques we find the
NEOS services very useful.
We are using the NEOS Server for verifying an algorithm designed for
solving a special 0-1 ILP problem. You can find our 0-1 ILP Model
in the following reference:
F Ghasemzadeh, N Archer and P Iyogun; A zero-one model for project portfolio selection and scheduling, Journal of Operations Research Society(1999) 50, 745-755
The application is a DSS based on this model.You can find more info in two last sections of the following paper and reference 3 of it.
I have modeled a seat assignment problem into the min-cost flow problem
and submitted data to the NEOS solver.
Cisco Systems
We have been doing research on System Identification techniques via an NLP
based maximum entropy formulation. We use system i/o data to determine the
underlying parameters for the following LTI system:
x(t+1) = Ax(t) + Bu(t)
y(t) = Cx(t)
In our case, the u's represent new customers for telecommunications
services. The y's represent their observed state. We seek to determine
A,B,C, and x to forecast future purchasing behavior from knowledge of u and
y.
The NLP formulation was one of 4 techniques we examined. We found that the formulation did not work too well for our problem. The main reason was that some of the matrix parameters must be quite small, making the problem difficult for most solvers. The equality constraints also caused problems in finding a feasible solution. We found that only LOQO would provide successful runs. Also, the predictive capability of the solution turned out to be not as good as some other techniques we examined. This result is probably application specific. I suspect applications with less extreme requirements for parameter values might work quite well.
We are using the NEOS server for testing our NLP formulations for generating
financial scenarios and for testing the performances of different NLP
solvers.
I use this site to run optimizations of selections
of prospects to solicit for refinancing mortgage loans.
I typically mail 770,000 - 800,000 offers per week from a weekly available to mail universe of 1.7MM-2.0MM consumers. I seek to maximize the expected revenue from the mail stream by combining response rate and revenue generated.
I am self taught in AMPL and quickly outgrew the student's version which came with Fourer's terrific book. I really appreciate having the horsepower available to run my optimizations. I now complete in 5-10 seconds what took one of my subordinates 3-4 days each week to do manually.
Keep up the good work and PLEASE PLEASE keep this site
open to the public.
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Science & Industry |
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We used NEOS to solve nonlinear optimization problems associated with
models of physical properties in chemistry. Our models were functions
involving variables (call topological indices). A typical function has
a constant term plus a sum of terms each of which has a coefficient
times a variable raised to a power. FILTER adjusted the constant term,
the coefficients, and the powers to minimize our objective function.
Our objective function was the sum of squares of the differences between
the experimental value of a physical property and the value predicted by
our model function.
Our first paper "Boiling Point Models of Alkanes" has been accepted for publication in the journal MATCH which publishes papers in Mathematical Chemistry. Our current project involves the study of melting points of chemical molecules of interest in the production of synthetic diesel fuel. This diesel fuel project was motivated by discussions that I had with a chemical engineer at the University of Pittsburgh.
I am using neos server to solve a polyfilm mill rolls slitting problem.
I'm working in the IT dept of Dubai PolyFilm (DPF) manufacturing plant,
in Dubai. I'm requested to find a solution that minimizes the slitting
waste. The mill rolls are of different sizes (different production
machines), and are of limited stock quantities.
I altered the example model that you provide on your site to be able to
have multiple stock, and currently I'm trying to validate it and execute
it on your neos server.
I am using your xpress solver to solve integer linear programming models
built during my research work. At the end of the research my work will be
submitted for publication.
I am a Petroleum Engineer and now I am working at my MSc. degree Thesis at
North Fluminense University, in Macaé - Rio de Janeiro, Brazil.
My MSc. Thesis is about Optimization of the gas balance planning in a
production system that all the platforms are interlinked in a complex
pipeline network.
First I want to thanks a lot for your contribution in my academic study
clearing questions about optimization solvers of NEOS.
I would like to send my congratulations for your excellent work in the NEOS
Server.
Your NEOS server has been of great help for us,
We are working on bi-dimensional modeling of earth's
conductivity distribution. We are testing new modeling
techniques based on quadratic and also linear programming.
We are a research center at Ensenada, Mexico, and our
work is on applied research and education. Currently we use
Knitro with the AMPL language.
The NEOS servers is useful for me to benchmark different optimization software.
I am using NEOS to compare the efficiency of my code with some codes,
such as LOQO, LANCELOT, SNOPT, MINOS, .., when they solve nonlinearly
constrained nonlinear network problems. It is research work for me.
I have extensively used your solver PCx to answer the question:
can a linear combination of knowledge-based potentials be used as
a fitness function in a genetic algorithm to predict the native
folding of a globular protein? The NEOS server is very useful
because it allows to save the time necessary in programming
optimisation methods.
I have used NEOS with LOQO solver to optimize an
interpolator. An interpolator is a device which
is used to estimate the values between two adjacent samples. My domain is
digital receivers where the receiver clock is not changed to match the
transmitter clock so one needs an interpolator to find the necessary
in-between samples. The interpolator will be used in a fractional
delay filter. Normally delay filters work with integer
delays; for my purposes I need to be able to delay by 0 < x < 1.
This is for R&D purposes [relating to
LAN/WAN systems].
I've been using NEOS lately to compare performance of
various NLP algorithms that utilize second order information.
We're a business of course, but this usage is a mixture of
commercial and research work.
I've been testing Knitro and filter and will use other NLP codes as time and bandwidth permit.
Thanks for providing this useful service.
I have been using NEOS for circuit optimization
problems involving large number of complex constraints,
and my experience with NEOS is a very pleasant one.
In particular I have used MINLP and SNOPT. The constant
monitoring of the optimization problems being carried out
is noteworthy and I especially thank the staff for
killing my jobs from time to time and for making
Kill Job facility available to users.
Our company is working with various projects concerning R&D
of internal combustion engines for cars and brakes for heavy vehicles.
For the past several years I have been working on
a system for protein structure prediction. As part of my system, I had
need to incorporate a nonlinear programming solver to handle packing
of sidechain atoms in the protein.
I modified my code to output packing subproblems directly in AMPL, which I could then submit to NEOS. In this fashion, I was able to evaluate solutions provided by different nonlinear solvers (I tried DONLP2, LOQO, FILTER, KNITRO, and LANCELOT), in effect testing the code before deciding which to acquire and attempt to link into my system.
NEOS is a great resource for people like me. Keep up the good work!
I have been using NEOS for circuit optimization
problems involving large number of complex constraints,
and my experience with NEOS is a very pleasant one.
In particular I have used MINLP and SNOPT. The constant
monitoring of the optimization problems being carried out
is noteworthy and I especially thank the staff for
killing my jobs from time to time and for making
Kill Job facility available to users.
I wish to extend my regards to your extraordinary work. I have just
gone through the text associated with the site and I found it very
interesting and so much related to my work. I should have told you
that I'm an electrical power engineer involved in the optimization
of medium and high voltage power systems. I build mathematical
models with either technical, economical, or hybrid objectives
and use numerical optimization algorithms to find the optimal
design parameters of power systems.
NEOS is really cool!
I am a die-hard GAMS user and would like to see GAMS interfaces
to NLP and MINLP solvers, as my interest is primarily in solving
nonlinear chemical engineering problems (production planning,
scheduling, etc.)
Keep up the good work!
Just discovered your great site. I have a problem arising in biophysics
in which I need to find the center of a polytope generated by an LP
problem (or equivalently all the vertices).
I am
using the LOQO solver and code written in
AMPL to perform numerical optimization of a spinor Bose-Einstein condensate.
This yields the ground state energy of the atomic system and the corresponding
wave functions as well as a variety of other properties of superfluids. The aim
is to develop a fundamental theory which can explain the recent observations of
Bose-Einstein condensates.
I have used NEOS as an excellent guide to optimisation methods and locating
associated software. Its the best resource I know of on the web and has been
very useful in the development of optimisation methods in our process
modeling software. Therefore, I welcome any developments to improve the
site.
AspenTech Ltd
We believe the NEOS optimization server provides a very
valuable service.
ABAQUS/Design Development Manager
Hibbitt, Karlsson & Sorensen, Inc.
We are using the NEOS Server for solving linear and nonlinear
complementarity problems
in engineering mechanics and in robotics (till now, mainly unilateral
contact problems
and friction).
The problem we are considering is the design of a yagi antenna. These antennas
consist of an array of wires and are frequently used as TV antennas.
In the 1960s a
lot of research has been done on the best design of this type of
antenna. However,
all research was experimental and therefore very costly and time
consuming. Our idea
is trying to design antennas by using the computer as a tuning
device, i.e. starting
from an initial design to have the computer finding the optimal
solution by using
constrained optimization methods. If this approach works, it
could be used for the
design of the future Square Kilometer Phased Array (SKA) for
radio astronomy to look
back in time to the first moments of the universe, which is to
be build in about 10
years from now.
We have tried various solvers on NEOS to see if this is possible at all and the yagi antenna has been used as a test case for which good validation is possible. The NEOS server offers a lot flexibility and various (well-known) solvers. It gives us the opportunity to find out which approach works best. Without this server it would probably be impossible to find out what strategy is most likely to succeed. Preliminary results are very encouraging for this approach.
I would like to express my support for this service. I am using this
server to solve a non-linear optimization problem to determine the
resource requirements for broadband networks using effective and
decoupling bandwidths. The objective function in my optimization is
assumed to be linear. The constraints are non-linear, exponential and
sometimes conditional.
The NEOS server helped me tremendously, since my background in optimization is weak. I was nevertheless able to further my research using this service
I just used AMPL-MINOS to solve an LP
arising from a stochastic programming application
that Jeff and I are looking at. The debug-resubmit
process could not have been simpler nor more convenient.
Fine stuff.
Here at our group at the Philips Research Laboratories we have used the
NEOS Server in our search for nonlinear optimization methods for circuit
simulation purposes.
I just found NEOS while looking around for a solution to my problem
(forgive the pun) attempting to optimize a couple of functions for a
computer game I am designing. It's very helpful, thank you
I am using the NEOS Server to solve optimization problems that arise in
(1) distance geometry and multidimensional scaling; and (2) design of
experiments.
We have used the NEOS server to solve NLP problems we formulated from
Integrated Circuits Computer Aided Design. And we plan to use it again
in the near future.
I have been using your AMPL front end and solvers to develop an
assignment problem.
BTW, this is a great service; allows me to develop without incurring
client costs or requesting software my university cannot afford.
I used your codes (Minpack) in the past. Any deployment of
nonlinear methods on a server are beneficial and their importance
will increase.
Thank you for your help. NEOS is very useful to me : I am solving huge
multi-commodity flow problems written in AMPL, and we do not have AMPL
available here. I have been using NEOS for solving multi-commodity flow problems arising
in the optimization of weights for routing in the Internet.
Congratulations for this nice tool and your continuous efforts to improve it.
I did send problems to the PCx and the BPMPD solver and
was very pleased with the outcome. These were rather small problems
in the field of chip design. Larger problems consumed too much
computer memory, let alone the time a solution might have taken.
Nevertheless, information is well categorized, easily available and very supportive, as well as the people involved are. I had misunderstood the right-hand-side labels of the MPS-format. Not realizing that they supported different versions, I thought each RHS had a different label. I reported the resulting output as not good and by the time I noticed my mistake, one of you pointed it out to me as well. Good luck with your efforts in making the NEOS server even better.
I have used some NLP solver from NEOS to solve a circuit optimization
problem. It's very helpful to use it this way, other than installing
those packages by myself.
By way of introduction let me mention that as a sideline to my professorial
duties, I maintain a web site which seeks to direct people to appropriate
parts of mathematics; my intended audience is students and professionals who
have at least a couple of years exposure to college level mathematics.
Turn to http://www.math-atlas.org/welcome.html and you'll see a set of blobs on the screen; there's also one on each index page e.g. http://www.math-atlas.org/index/15-XX.html . The positions of these blobs were determined by the NEOS server. I was happy to have access to the server because I think having the blobs positioned appropriately helps understand the topic, and therefore adds to the quality of the web pages.
What these blobs are is sets of papers published in mathematics (specifically, papers reviewed in Mathematical Reviews 1980-1999). Each paper in MR is assigned one or more classification codes from a subject classification system of mathematics. I used the incidence data showing how many papers published in various sub-disciplines were given secondary classifications in other sub-disciplines; these data gave a sort of metric on the subject areas, which indicates that say Group Theory is close to Ring Theory but far from Differential Equations. So conceptually I then have the various disciplines arrayed in some high-dimensional space, some pairs of them closer to each other than other pairs. In my mind I visualize the subjects hovering around like stars in the Milky Way galaxy.
Well, there are standard tools for projecting such a picture to a plane so as to show the distance relationships optimally -- that is, you can sort of figure out the "main plane" of the galaxy. The problem is that when you project the various blobs to the plane of the galaxy, some of them will obscure others which are directly above or below them.
So here's where I used NEOS: I took the nominal positions of the different blobs and asked for the minimal amount of jiggle I would need to separate them on the plane. It's not a hard project, conceptually, and I imagine cartographers have packaged routines to deal with this. But certainly there were too many variables and constraints to allow an analytic solution (and way too much computation to appeal to a theoretician like me). It took me a little while to master the NEOS syntax (e.g. I had to remember to tell it to display the answer...) but once I got it down to a science I was able to have the server supply the results I wanted in a painless way.
There's quite a bit of arbitrariness in the way the data are massaged to
produce a picture: one shouldn't try to read too much into these images.
On the other hand, when left to their own devices, the programs tended to
draw pictures which corroborated what I would have drawn on my own (when I
had some prior knowledge of a sub-discipline) and gave hints about what
real connections existed in sub-disciplines with which I was not familiar.
So I'm quite happy with the results so far.