Simulation Optimization Library

Welcome to SimOpt! is a testbed of simulation-optimization problems. The purpose of the testbed is to encourage development and constructive comparison of simulation-optimization techniques and algorithms. We are particularly interested in increasing attention on the finite time performance of algorithms, rather than the asymptotic results that one often finds in related literature.

For the purposes of this site, we define simulation as a very general technique for estimating statistical measures of complex systems. A system is modeled as if the random variables were known. Then values for the variables are drawn randomly from their known probability distributions. Each replication gives one observation of the system response. By simulating a system in this fashion for many replications and recording the responses, one can compute statistics concerning the results. The statistics are used for evaluation and design.

The Problems Library contains a variety of test problems for simulation optimization. You can also share your test problems by uploading a problem to this site. Detailed instructions can be found through the Upload page.

The paper

Pasupathy, R., and S. G. Henderson. 2006. A testbed of simulation-optimization problems. Proceedings of the 2006 Winter Simulation Conference. L. F. Perrone, F. P. Wieland, J. Liu, B. G. Lawson, D. M. Nicol, and R. M. Fujimoto, eds. 255-263

explains the original motivation for the testbed. A followup article in 2011 describes the (voluntary but desired) interface for matlab implementations of problems.

The Solver Library is intended to provide users with the latest simulation optimization solvers to solve different types of simulation optimization problems. It is also intended to help researchers compare existing solvers on different SO problems. Instructions on how to run solver code on problem code can be found here.

This website was developed through work supported by the National Science Foundation under Grant Nos. DMI-0400287, CMMI-0800688 and CMMI-1200315. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).

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