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Quadratic assignment problem Vehicle routing problem also at HEC Traveling salesman Graph partitioning Quantified Boolean formulas Constraint solvers Shortest paths Mixed integer programming Train timetabling Set covering and packing Beasley's OR library with many problems Maximum clique, Maximum independent set, minimum vertex cover, vertex coloring ...


Here is a start. Please add to this. BOLIB: Bilevel Optimization LIBrary of Test Problems https://eprints.soton.ac.uk/436854/1/BOLIBver2.pdf CBLIB: The Conic Benchmark Library: http://cblib.zib.de/ . Twitter at https://twitter.com/cblibtw COMPlib: COnstraint Matrix-optimization Problem library (Nonlinear SDPs, control system design, and related problems) ...


Some more libraries: Biq Mac Library: a Binary quadratic and max cut Library: http://biqmac.uni-klu.ac.at/biqmaclib.html OR Library: a collection of test data sets for a variety of Operations Research problems: http://people.brunel.ac.uk/~mastjjb/jeb/info.html SIPLIB: a collection of stochastic integer programming problems: https://www2.isye.gatech.edu/~...


There is a paper of Ahammed and Moscato on finding hard instances for Concorde using Lindenmeyer systems. They were able to find small instances with about 1500 cities that took (in 2011) more than 4 hours to solve. One should probably add that "hard" always means "hard for some algorithm". So, for balance, here is a paper of Kate Smith-Miles & van ...


Some other libraries (mainly for MINLP) are: MINLP-Lib. PrincetonLib.


There are at least three more problem libraries that you can access. OR-Lib has instances of Quadratic Assignment/Knapsack/Minimum spanning tree that you can use. MINLP-Lib has several QP, BQP, IQP instances that you can filter by convexity. PrincetonLib chapter 2 problems. I think that you can apart of it come up with synthetic instances which are not ...


Some more: Atamturk datasets on fixed-charge flow, lot sizing, mixed-integer knapsack, and more Combinatorial Auction Test Suite (CATS) National Traveling Salesman Problems VLSI data sets: Another collection of 102 TSP instances GiC Data Sets Update: I made a GitHub repository and added all of these references. there.


Some libraries for stochastic programming test problems may be found in Jeff Linderoth, Alex Shapiro, and Stephen Wright (2002) POSTS: A (PO)rtable (S)tochastic programming (T)est (S)et (Derek Holmes and John Birge) Test-Problem Collection for Stochastic Linear Programming (Andy Felt) SIPLIB: A (S)tochastic (I)nteger (P)rogramming Test Problem (LIB)rary (...


There is a paper by Papadimitriou and Steiglitz here to construct instances, which are very hard for local searches to find optimal solution.


You can reformulate Quadratic Programs as Second Order Conic Programs (SOCPs). Therefore, you can use many conic benchmark libraries and filter SOCPs. For example, Conic Benchmark Library can be a good start!


Would these be helpful? 1) OptaPlanner examples problem definitions and data sets Original problems: cloud balancing, dinner party, tennis club scheduling, meeting scheduling, task assigning, investment portfolio optimization, conference scheduling, rock tour, flight crew scheduling Problems defined by academic challenges and others: tsp, course scheduling ...


For a test problem, check manually (outside GAMS) that the solution satisfies all constraints. If not, your GAMS model may be wrong. If all constraints are satisfied, try using a different solver and see if the same objective value is achieved. If the other solver gets a better result, your current runs may be stopping short of optimality. If the objective ...


Collecting things in a parameter is actually very simple. set run /.../; parameter objresult(run,*); loop(run, solve m .... objresult(run,"obj") = m.objval; objresult(run,"bestbound") = m.objest; objresult(run,"absgap") = abs(m.objval-m.objest); );


Pantelis, It is a great detriment that no such collection of examples exists. One problem is that there is no established format for multistage problems like MPS. (There is SMPS [paper], but this doesn't scale to the types of problems we typically solve with $10^{40}$ leaf nodes in a scenario tree.) I have been collecting a number of examples in the SDDP....


"Ruszczynski, Andrzej, and Robert J. Vanderbei. "Frontiers of stochastically nondominated portfolios." Econometrica 71.4 (2003): 1287-1297". This paper provides a large number of test problems which for example were used for testing purpose in "Dentcheva, Darinka, and Andrzej Ruszczyński. "Portfolio optimization with stochastic dominance constraints." ...


You can check the Test Sets section of the Stochastic Programming Resources web site. It contains different types of problems—two-stage or multi-stage, mixed or pure IP, and even LP in the different stages. Hopefully, you should find something close to the problem type you are looking for.


You cannot loop over include files ($include is compile-time, while loop is execution- time, this is similar to say C where you cannot loop over #include). One could loop over complete GAMS models (call gams inside a loop), or over reading data from GDX (GAMS data) files. But often a better approach is the following. I would just read in all problem data in ...


There is a good description of different problem instances here. From the link: ...benchmark problems (Solomon, 1987) composed of six different problem types (C1,C2,R1,R2,RC1,RC2). Each data set contains between eight to twelve 100-node problems. The names of the six problem types have the following meaning. Sets C have clustered customers whose time ...


There is also: GasLib, with gas network instances based on perturbed real-world data.

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