Feasibility Determination in Presence of Multiple Performance Measure Constraints

Siyang Gao; Weiwei Chen

doi:10.1109/ICIT.2016.7474887

Feasibility Determination in Presence of Multiple Performance Measure Constraints

Siyang Gao^*, Weiwei Chen

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

A lot of problems in control engineering aim at solving discrete-event systems in presence of performance measure constraints. In many cases, these problems are most suitable to be modeled as constrained simulation optimization, and a key question for solving these problems is to efficiently and accurately select all the feasible designs from a finite set of design alternatives. In this paper, we consider the feasibility determination problem in presence of multiple performance measure constraints. By making some asymptotic approximation, we derive the optimal solution to maximize the expected number of correct selection for all the designs. A corresponding sequential selection procedure is designed for implementation. Numerical testing shows that our approach considerably enhances the simulation efficiency.

Original language	English
Title of host publication	Proceedings of the 2016 IEEE International Conference on Industrial Technology
Publisher	IEEE
Pages	988-992
ISBN (Electronic)	978-1-4673-8075-1
DOIs	https://doi.org/10.1109/ICIT.2016.7474887
Publication status	Published - Mar 2016
Event	The 2016 IEEE International Conference on Industrial Technology - , Taiwan, China Duration: 14 Mar 2016 → 17 Mar 2016

Conference

Conference	The 2016 IEEE International Conference on Industrial Technology
Place	Taiwan, China
Period	14/03/16 → 17/03/16

Research Keywords

SIMULATION BUDGET ALLOCATION
SELECTION
SUBSET

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title = "Feasibility Determination in Presence of Multiple Performance Measure Constraints",

abstract = "A lot of problems in control engineering aim at solving discrete-event systems in presence of performance measure constraints. In many cases, these problems are most suitable to be modeled as constrained simulation optimization, and a key question for solving these problems is to efficiently and accurately select all the feasible designs from a finite set of design alternatives. In this paper, we consider the feasibility determination problem in presence of multiple performance measure constraints. By making some asymptotic approximation, we derive the optimal solution to maximize the expected number of correct selection for all the designs. A corresponding sequential selection procedure is designed for implementation. Numerical testing shows that our approach considerably enhances the simulation efficiency.",

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language = "English",

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booktitle = "Proceedings of the 2016 IEEE International Conference on Industrial Technology",

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AU - Chen, Weiwei

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N2 - A lot of problems in control engineering aim at solving discrete-event systems in presence of performance measure constraints. In many cases, these problems are most suitable to be modeled as constrained simulation optimization, and a key question for solving these problems is to efficiently and accurately select all the feasible designs from a finite set of design alternatives. In this paper, we consider the feasibility determination problem in presence of multiple performance measure constraints. By making some asymptotic approximation, we derive the optimal solution to maximize the expected number of correct selection for all the designs. A corresponding sequential selection procedure is designed for implementation. Numerical testing shows that our approach considerably enhances the simulation efficiency.

AB - A lot of problems in control engineering aim at solving discrete-event systems in presence of performance measure constraints. In many cases, these problems are most suitable to be modeled as constrained simulation optimization, and a key question for solving these problems is to efficiently and accurately select all the feasible designs from a finite set of design alternatives. In this paper, we consider the feasibility determination problem in presence of multiple performance measure constraints. By making some asymptotic approximation, we derive the optimal solution to maximize the expected number of correct selection for all the designs. A corresponding sequential selection procedure is designed for implementation. Numerical testing shows that our approach considerably enhances the simulation efficiency.

KW - SIMULATION BUDGET ALLOCATION

KW - SELECTION

KW - SUBSET

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DO - 10.1109/ICIT.2016.7474887

M3 - RGC 32 - Refereed conference paper (with host publication)

SP - 988

EP - 992

BT - Proceedings of the 2016 IEEE International Conference on Industrial Technology

PB - IEEE

T2 - The 2016 IEEE International Conference on Industrial Technology

Y2 - 14 March 2016 through 17 March 2016

ER -

Feasibility Determination in Presence of Multiple Performance Measure Constraints

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