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Handling stochastic constraints in discrete optimization via simulation

Authors:

Chuljin Park,

Seong-Hee KimAuthors Info & Claims

WSC '11: Proceedings of the Winter Simulation Conference

Pages 4217 - 4226

Published: 11 December 2011 Publication History

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Abstract

We consider a discrete optimization via simulation problem with stochastic constraints on secondary performance measures where both objective and secondary performance measures need to be estimated by simulation. To solve the problem, we present a method called penalty function with memory (PFM), which determines a penalty value for a solution based on history of feasibility check on the solution. PFM converts a DOvS problem with stochastic constraints into a series of new optimization problems without stochastic constraints so that an existing DOvS algorithm can be applied to solve the new problem.

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Cited By

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Feldman GHunter SPasupathy R(2015)Multi-objective simulation optimization on finite setsProceedings of the 2015 Winter Simulation Conference10.5555/2888619.2889104(3610-3621)Online publication date: 6-Dec-2015
https://dl.acm.org/doi/10.5555/2888619.2889104
Hu LAndradóttir SBuckley SMiller J(2014)A penalty function approach for simulation optimization with stochastic constraintsProceedings of the 2014 Winter Simulation Conference10.5555/2693848.2694313(3730-3736)Online publication date: 7-Dec-2014
https://dl.acm.org/doi/10.5555/2693848.2694313
Nagaraj KPasupathy RHill RKuhl M(2013)R-SPLINE for local integer-ordered simulation optimization problems with stochastic constraintsProceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World10.5555/2675983.2676091(846-855)Online publication date: 8-Dec-2013
https://dl.acm.org/doi/10.5555/2675983.2676091

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Handling stochastic constraints in discrete optimization via simulation

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WSC '11: Proceedings of the Winter Simulation Conference

December 2011

4336 pages

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Winter Simulation Conference

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Published: 11 December 2011

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WSC'11: Winter Simulation Conference 2011

December 11 - 14, 2011

Arizona, Phoenix

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WSC '11 Paper Acceptance Rate 203 of 270 submissions, 75%;

Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

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Feldman GHunter SPasupathy R(2015)Multi-objective simulation optimization on finite setsProceedings of the 2015 Winter Simulation Conference10.5555/2888619.2889104(3610-3621)Online publication date: 6-Dec-2015
https://dl.acm.org/doi/10.5555/2888619.2889104
Hu LAndradóttir SBuckley SMiller J(2014)A penalty function approach for simulation optimization with stochastic constraintsProceedings of the 2014 Winter Simulation Conference10.5555/2693848.2694313(3730-3736)Online publication date: 7-Dec-2014
https://dl.acm.org/doi/10.5555/2693848.2694313
Nagaraj KPasupathy RHill RKuhl M(2013)R-SPLINE for local integer-ordered simulation optimization problems with stochastic constraintsProceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World10.5555/2675983.2676091(846-855)Online publication date: 8-Dec-2013
https://dl.acm.org/doi/10.5555/2675983.2676091

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Penalty Function with Memory for Discrete Optimization via Simulation with Stochastic Constraints

Efficient discrete optimization via simulation using stochastic kriging

Stochastic Dynamic Optimization with Discounted Stochastic Dominance Constraints

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Penalty Function with Memory for Discrete Optimization via Simulation with Stochastic Constraints

Efficient discrete optimization via simulation using stochastic kriging

Stochastic Dynamic Optimization with Discounted Stochastic Dominance Constraints

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