Tuesday, 14:15 - 14:40 h, Room: H 3503


Satyajith Amaran
A comparison of software and algorithms in unconstrained simulation optimization problems

Coauthors: Scott J. Bury, Nikolaos V. Sahinidis, Bikram Sharda


Over the last few decades, several algorithms for simulation optimization (SO) have appeared and, along with them, diverse application areas for these algorithms. The algorithmic approaches proposed in the literature include ranking and selection, sample average approximation, metaheuristics, response surface methodology and random search. Application areas range from urban traffic control to investment portfolio optimization to operation scheduling. However, a systematic
comparison of algorithmic approaches for simulation optimization problems from the literature is not available. At this juncture in the evolution of SO, it is instructive to review the size and kinds of problems handled as well as the performance of different classes of algorithms, both in terms of
quality of solutions and number of experiments (or function evaluations) required. In this work, we use a library of diverse algorithms, and propose a method to assess their performance under homogeneous and heterogeneous variances on a recently-compiled simulation optimization test set. Discussions follow.


Talk 3 of the invited session Tue.2.H 3503
"New techniques for optimization without derivatives" [...]
Cluster 6
"Derivative-free & simulation-based optimization" [...]


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