Title

Using Clustering Analysis For Decision-Making With Multiple Stochastic Objectives

Keywords

Cluster analysis; Decision making; Pareto analysis; Stochastic objectives

Abstract

A number of researchers have successfully integrated stochastic computer simulation models with combinatorial optimization procedures that generate solutions for decision-makers. These integrated approaches often use nature inspired search heuristics that also possess a stochastic feature of their own. These integrated simulation optimization approaches have been primarily designed to address single objective optimization problems. Only a few approaches have been designed for multiobjective optimization where they generate a finite set of Pareto optima. This Pareto optimal set often contains a very large number of solutions, which could be overwhelming to the decision-maker. In this paper, an innovative approach that effectively reduces the number of the solutions while considering the stochastic nature of the objective functions is proposed. A detailed description of the proposed approach and a numerical example that demonstrates the performance are provided.

Publication Date

1-1-2013

Publication Title

IIE Annual Conference and Expo 2013

Number of Pages

2828-2837

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

84900333604 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84900333604

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