Journal Article10.1080/07408179608966291
An interactive multiple-response simulation optimization method
Carolyn R. Boyle,Wan S. Shin +1 more
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TL;DR: This study proposes a new interactive multicriteria method for determining the best levels of the decision variables needed to optimize a stochastic computer simulation with multiple response variables that combines good features from interactive multiple objective mathematical programming and response surface methodology.
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Abstract: This study proposes a new interactive multicriteria method for determining the best levels of the decision variables needed to optimize a stochastic computer simulation with multiple response variables. The method, called the Pairwise Comparison Stochastic Cutting Plane (PCSCP) method, combines good features from interactive multiple objective mathematical programming and response surface methodology. The major characteristics of the PCSCP method are: (1) it interacts progressively with the decision-maker (DM) to obtain her preferences, (2) it uses experimental design to explore the decision space adequately while reducing the burden on the DM, and (3) it uses the preference information provided by the DM and the sampling error in the responses to reduce the decision space. The mechanics of the method are illustrated with a numerical example. Some computational studies evaluating the method are also reported.
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Citations
A general framework for multiresponse optimization problems based on goal programming
TL;DR: This study proposes a general framework in MRS problems according to some existing works and some types of related decision makers and attempts to aggregate all of characteristics in one approach.
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An Overview of Optimization Formulations for Multiresponse Surface Problems
TL;DR: The foremost approaches in multiresponse optimization are categorized and integrated, and guidelines are presented to help select appropriate formulations.
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Multiresponse systems optimization using a goal attainment approach
TL;DR: A goal attainment approach to optimize multiresponse systems is presented that aims to identify the settings of control factors to minimize the overall weighted maximal distance measure with respect to individual response targets.
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Optimization of correlated multiple responses of ultrasonic machining (USM) process
TL;DR: In this article, two sets of past experimental data on USM process are analyzed using three methods dealing with the multiple correlated responses, and the optimization performances of these three methods are subsequently compared.
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Optimization of systems with multiple performance measures via simulation: Survey and recommendations
TL;DR: This paper focuses specifically on the simulation optimization problem that involves multiple performance measures and surveys available methodologies for this problem and discusses notable strengths and weaknesses of each.
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