ACM Transactions on Modeling and Computer Simulation (TOMACS)
A Multiple Attribute Utility Theory Approach to Ranking and Selection
Management Science
Proceedings of the 38th conference on Winter simulation
Discrete Optimization via Simulation Using COMPASS
Operations Research
A framework for locally convergent random-search algorithms for discrete optimization via simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Multi-objective genetic algorithms: Problem difficulties and construction of test problems
Evolutionary Computation
Industrial strength COMPASS: A comprehensive algorithm and software for optimization via simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulation optimization using the cross-entropy method with optimal computing budget allocation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Unlocking value from component exchange contracts in aviation using simulation-based optimisation
Proceedings of the Winter Simulation Conference
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Due to its wide application in many industries, discrete optimization via simulation (DOvS) has recently attracted more research interests. As industry systems become more complex, advanced search algorithms for DOvS are desired with higher expectation towards efficiency. In this research work, we combine the ideas of single-objective Convergent Optimization via Most-Promising-Area Stochastic Search (COMPASS) with the concept of Pareto optimality to propose multi-objective (MO) MO-COMPASS for solving DOvS problems with two or more objectives. Numerical experiments are illustrated to show its ability to achieve high efficiency.