Ranking, selection and multiple comparisons in computer simulations
WSC '94 Proceedings of the 26th conference on Winter simulation
A gradient approach for smartly allocating computing budget for discrete event simulation
WSC '96 Proceedings of the 28th conference on Winter simulation
Selecting the best system: a decision-theoretic approach
Proceedings of the 29th conference on Winter simulation
New development of optimal computing budget allocation for discrete event simulation
Proceedings of the 29th conference on Winter simulation
Statistical screening, selection, and multiple comparison procedures in computer simulation
Proceedings of the 30th conference on Winter simulation
An approach to ranking and selection for multiple performance measures
Proceedings of the 30th conference on Winter simulation
Multivariate ranking and selection without reduction to a univariate problem
WSC '78 Proceedings of the 10th conference on Winter simulation - Volume 1
ACM Transactions on Modeling and Computer Simulation (TOMACS)
A Multiple Attribute Utility Theory Approach to Ranking and Selection
Management Science
Special topics on simulation analysis: better-than-optimal simulation run allocation?
Proceedings of the 35th conference on Winter simulation: driving innovation
An overview of evolutionary algorithms in multiobjective optimization
Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Application of multi-objective simulation-optimization techniques to inventory management problems
WSC '05 Proceedings of the 37th conference on Winter simulation
Proceedings of the 38th conference on Winter simulation
Using multi-criteria modeling and simulation to achieve lean goals
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Multi-objective simulation optimization through search heuristics and relational database analysis
Decision Support Systems
A multi-objective selection procedure of determining a Pareto set
Computers and Operations Research
Some topics for simulation optimization
Proceedings of the 40th Conference on Winter Simulation
A preliminary study of optimal splitting for rare-event simulation
Proceedings of the 40th Conference on Winter Simulation
Research advances in automated red teaming
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
Optimal computing budget allocation for constrained optimization
Winter Simulation Conference
Research issues in symbiotic simulation
Winter Simulation Conference
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Simulation plays a vital role in identifying the best system design from among a set of competing designs. To improve simulation efficiency, ranking and selection techniques are often used to determine the number of simulation replications required so that a pre-specified level of correct selection is guaranteed at a modest possible computational expense. As most real-life systems are multi-objective in nature, in this paper, we consider a multi-objective ranking and selection problem, where the system designs are evaluated in terms of more than one performance measure. We incorporate the concept of Pareto optimality into the ranking and selection scheme, and try to find all of the non-dominated designs rather than a single "best" one. A simple sequential solution method is proposed to allocate the simulation replications. Computational results show that the proposed algorithm is efficient in terms of the total number of replications needed to find the Pareto set.