Single- And Multi-Objective Ranking and Selection Procedures in Simulation: A Historical Review

Abstract

Ranking and selection (R&S) procedures form an important research field in computer simulation and its applications. In simulation, one usually has to select the best from a number of scenarios or alternative designs. Often, the simulated processes have a stochastic nature, which means that, to distinguish alternatives, they must exhibit significant statistical differences. R&S procedures assist the decision-maker with the selection of the best alternative with high confidence. This paper reviews past and current R&S procedures. The review traces back to the 1950s, when the first R&S procedure was proposed, and discusses the various R&S procedures proposed since then to the present day, presenting a cursory view of the research in the area. The review includes studies in both the single-objective and the multi-objective domains. It presents the research trend, discusses specific issues, and gives recommendations for future research in both domains. OPSOMMINGRangorde-en keuseprosedures (R&K) vorm 'n belangrike navorsingsveld in rekenaarsimulasie en -toepassings. Simulasiestudies vereis gewoonlik dat die beste kandidaat van 'n aantal scenarios of alternatiewe ontwerpe gekies moet word. Die gesimuleerde prosesse is gewoonlik van 'n stogastiese aard, en hulle moet statisties-beduidend verskil ten einde onderskeid te kan tref. R&K prosedures ondersteun die besluitnemer om die beste alternatief met groot vertroue te kies. Hierdie artikel verskaf 'n resensie van vroeë en huidige R&K prosedures. Die ondersoek strek terug tot in die 1950s toe die eerste R&K prosedures voorgestel is, en bespreek die verskeie R&K prosedures wat sedertdien ontwikkel is, terwyl 'n oorsigtelike blik op die navorsingsveld gegee word. Die resensie sluit studies in beide enkel-en multidoelwitdomein in. Dit bespreek navorsingsneigings en spesifieke kwessies, en maak voorstelle vir verdere navorsing in beide domeins. INTRODUCTIONComputer simulation is a powerful and essential tool in modern society to improve the operation of current systems and business practices. It contributes to the efficient management of processes and systems -the main focus of many industrial engineers -by providing a what-if analysis. In operating a system, one often faces a situation where the following question arises: If some changes were made to the current parameter settings (or decision variables) 1 in the operation of the system, what would happen? Would they result in a better performance of the system or not? It is usually not easy to estimate the effect of the changes because the system is often complex and exhibits a stochastic nature. Simulation helps decision-makers in such cases by simulating the real system and providing the estimates of system performance measures. One can compare the performance of the simulated 1 Various terms are used in simulation to indicate parameter settings of the system: system designs, systems, designs, scenarios, and/or alternatives. The term population is also used in the same context in statistics.

Development of a Discrete-Event, Stochastic Multi-Objective Metaheuristic Simulation Optimisation Suite for a Commercial Software Package

“…We present in this work the development of an SO DSS tool that can be integrated into commercial simulation software to solve MOO problems in stochastic systems. We recognise that powerful commercial packages like OptQuest exist, but we desire to develop a package including the novel procedures for ranking and selection from Yoon [4] in future.…”