Finding feasible systems in the presence of constraints on multiple performance measures

Authors:
Demet Batur;Seong-Hee Kim
Affiliations:
University of Nebraska-Lincoln, Lincoln, NE;Georgia Institute of Technology, Atlanta, Georgia
Venue:
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Year:
2010

Citing 6
Cited 7

A fully sequential procedure for indifference-zone selection in simulation

ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simple Procedures for Selecting the Best Simulated System When the Number of Alternatives is Large

Operations Research
A Multiple Attribute Utility Theory Approach to Ranking and Selection

Management Science
Statistical selection of the best system

WSC '05 Proceedings of the 37th conference on Winter simulation
Performance of variance updating ranking and selection procedures

WSC '05 Proceedings of the 37th conference on Winter simulation
On the Asymptotic Validity of Fully Sequential Selection Procedures for Steady-State Simulation

Operations Research

A brief introduction to optimization via simulation

Winter Simulation Conference
Simulation-based optimization over discrete sets with noisy constraints

Proceedings of the Winter Simulation Conference
Handling stochastic constraints in discrete optimization via simulation

Proceedings of the Winter Simulation Conference
Optimal sampling laws for constrained simulation optimization on finite sets: the bivariate normal case

Proceedings of the Winter Simulation Conference
Best-subset selection procedure

Proceedings of the Winter Simulation Conference
Large-deviation sampling laws for constrained simulation optimization on finite sets

Proceedings of the Winter Simulation Conference
Optimal Sampling Laws for Stochastically Constrained Simulation Optimization on Finite Sets

INFORMS Journal on Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We consider the problem of finding a set of feasible or near-feasible systems among a finite number of simulated systems in the presence of constraints on secondary performance measures. We first present a generic procedure that detects the feasibility of one system in the presence of one constraint and extend it to the case of two or more systems and constraints. To accelerate the elimination of infeasible systems, a method that reuses collected observations and its variance-updating version are discussed. Experimental results are presented to compare the performance of the proposed procedures.