Simulation Modeling and Analysis

Abstract

CONTENTS 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234 5.1.1 Utility Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234 5.1.1.1 Axioms of Utility Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 5.1.1.2 Example of Utility Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 5.1.1.3 Stochastic Dominance Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 5.1.2 Concept of Pareto Optimality and Its Significance . . . . . . . . . . . . . . . . . . . . . 238 5.1.3 Multiattribute Utility Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 5.1.3.1 Use of Goal Programming in MAUT . . . . . . . . . . . . . . . . . . . . . . . . 245 5.1.4 Multicriteria Decision Making . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246 5.1.5 Methods of MCDM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 5.1.5.1 Weighted Sum Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 5.1.5.2 Weighted Product Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 250 5.1.5.3 ANP and AHP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 250 5.1.5.4 Elimination and Choice-Translating Reality . . . . . . . . . . . . . . . . . . . 261 5.1.5.5 Preference-Ranking Organization Method for Enrichment Evaluations . 265 5.1.5.6 TOPSIS Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 5.1.5.7 VIKOR Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 5.1.5.8 Potentially All Pairwise Rankings of All Possible Alternatives . . . . . . . 272 5.1.5.9 Measuring Attractiveness by a Categorical-Based Evaluation Technique 274 5.1.5.10 Decision Trees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275 5.1.6 Other Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280 ABSTRACT This chapter will deal with different methodologies of decision making when the parametric as well as the nonparametric form of the objective functions are not known as this is quite possible in practical situations. The chapter starts with the definition of the utility theory with relevant examples. It then goes on to discuss the concept of Pareto principle and dwells into the idea of multiattribute utility theory (MAUT) and the relevance of goal programming with respect to MAUT. After building on this background, the basic tenets along with relevant examples for topics ranging from analytical network process, analytical hierarchy process, elimination and choice-translating reality method, preference-ranking organization method for enrichment evaluation, technique for order preference by similarity to ideal solution, and VIseKriterijumska Optimizacija I Kompromisno Resenje potentially all pairwise ranking of all possible alternatives, measuring attractiveness by a categorical based evaluation technique, decision trees, are discussed. Finally, the chapter ends with a list of softwares and urls, relevant to the topics covered in the chapter.