Industrial strength COMPASS:a comprehensive algorithm and software for optimization via simulation

Xu, Jie and Nelson, Barry L. and Hong, Jeff L. (2010) Industrial strength COMPASS:a comprehensive algorithm and software for optimization via simulation. ACM Transactions on Modeling and Computer Simulation, 20 (1). pp. 1-29. ISSN 1049-3301

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Abstract

Industrial Strength COMPASS (ISC) is a particular implementation of a general framework for optimizing the expected value of a performance measure of a stochastic simulation with respect to integer-ordered decision variables in a finite (but typically large) feasible region defined by linear-integer constraints. The framework consists of a global-search phase, followed by a local-search phase, and ending with a “clean-up” (selection of the best) phase. Each phase provides a probability 1 convergence guarantee as the simulation effort increases without bound: Convergence to a globally optimal solution in the global-search phase; convergence to a locally optimal solution in the local-search phase; and convergence to the best of a small number of good solutions in the clean-up phase. In practice, ISC stops short of such convergence by applying an improvement-based transition rule from the global phase to the local phase; a statistical test of convergence from the local phase to the clean-up phase; and a ranking-and-selection procedure to terminate the clean-up phase. Small-sample validity of the statistical test and ranking-and-selection procedure is proven for normally distributed data. ISC is compared to the commercial optimization via simulation package OptQuest on five test problems that range from 2 to 20 decision variables and on the order of 104 to 1020 feasible solutions. These test cases represent response-surface models with known properties and realistic system simulation problems.

Item Type:
Journal Article
Journal or Publication Title:
ACM Transactions on Modeling and Computer Simulation
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1706
Subjects:
ID Code:
65042
Deposited By:
Deposited On:
13 Jun 2013 10:25
Refereed?:
Yes
Published?:
Published
Last Modified:
24 Nov 2020 02:27