Discrete Optimization via Simulation Using COMPASS

We propose an optimization-via-simulation algorithm, called COMPASS, for use when the performance measure is estimated via a stochastic, discrete-event simulation, and the decision variables are integer ordered. We prove that COMPASS converges to the set of local optimal solutions with probability 1...

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Bibliographic Details
Published inOperations research Vol. 54; no. 1; pp. 115 - 129
Main Authors Hong, L. Jeff, Nelson, Barry L
Format Journal Article
LanguageEnglish
Published Linthicum, MD INFORMS 01.01.2006
Institute for Operations Research and the Management Sciences
Subjects
adaptive random search
Algorithms
Applied sciences
Compasses
Coordinate systems
Design of experiments
Exact sciences and technology
Flows in networks. Combinatorial problems
Integers
Iterative solutions
Markov chains
Objective functions
Observational research
Operational research and scientific management
Operational research. Management science
Operations research
Optimal solutions
Optimization
optimization via simulation
programming
Sample mean
Simulated annealing
Simulation
stochastic
Stochastic models
Studies
Experimental design
simulation
Discrete programming
Stochastic simulation
Discrete event simulation
Adaptive method
Optimization
stochastic: adaptive random search
Stochastic programming
Random search
design of experiments: optimization via simulation; programming
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Summary:We propose an optimization-via-simulation algorithm, called COMPASS, for use when the performance measure is estimated via a stochastic, discrete-event simulation, and the decision variables are integer ordered. We prove that COMPASS converges to the set of local optimal solutions with probability 1 for both terminating and steady-state simulation, and for both fully constrained problems and partially constrained or unconstrained problems under mild conditions.
ISSN:0030-364X
1526-5463
DOI:10.1287/opre.1050.0237