Paper Info
Title
Finding the pareto set for multi-objective simulation models by minimization of expected opportunity cost
Abstract
In this study, we mainly explore how to optimally allocate the computing budget for a multi-objective ranking and selection (MORS) problem when the measure of selection quality is the expected opportunity cost (OC). We define OC incurred to both the observed Pareto and non-Pareto set, and present a sequential procedure to allocate the replications among the designs according to some asymptotic allocation rules. Numerical analysis shows that the proposed solution framework works well when compared with other algorithms in terms of its capability of identifying the true Pareto set.
Year
DOI
Venue
2007
10.1109/WSC.2007.4419642
Winter Simulation Conference
Keywords
Field
DocType
multi-objective simulation model,non-pareto set,pareto set,expected opportunity cost minimization,multiobjective ranking,expected opportunity cost,multiobjective simulation model,numerical analysis,set theory,true pareto set,observed pareto,multiobjective selection,pareto optimisation,computing budget,multi-objective ranking,asymptotic allocation rule,optimal allocation,proposed solution framework,minimisation,selection quality,simulation model,opportunity cost
Set theory,Mathematical optimization,Pareto interpolation,Ranking,Computer science,Simulation modeling,Minification,Minimisation (psychology),Pareto principle,Opportunity cost
Conference
ISBN
Citations 
PageRank 
978-1-4244-1306-5
7
0.64
References 
Authors
10
3
Name
Order
Citations
PageRank
Loo Hay Lee1115993.96
Ek Peng Chew245944.07
Suyan Teng31136.92