Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/62202
Title: Comprehensive pareto efficiency in robust counterpart optimization
Authors: Shang, K
Feng, Z
Ke, L
Chan, FTS 
Keywords: Integer programming
Linear programming
Pareto optimality
Robust optimization
Issue Date: 2016
Publisher: Pergamon Press
Source: Computers and chemical engineering, 2016, v. 94, p. 75-91 How to cite?
Journal: Computers and chemical engineering 
Abstract: In this paper, an innovative concept named Comprehensive Pareto Efficiency is introduced in the context of robust counterpart optimization, which consists of three sub-concepts: Pareto Robust Optimality (PRO), Global Pareto Robust Optimality (GPRO) and Elite Pareto Robust Optimality (EPRO). Different algorithms are developed for computing robust solutions with respect to these three sub-concepts. As all sub-concepts are based on the Probability of Constraint Violation (PCV), formulations of PCV under different probability distributions are derived and an alternative way to calculate PCV is also presented. Numerical studies are drawn from two applications (production planning problem and orienteering problem), to demonstrate the Comprehensive Pareto Efficiency. The numerical results show that the Comprehensive Pareto Efficiency has important significance for practical applications in terms of the evaluation of the quality of robust solutions and the analysis of the difference between different robust counterparts, which provides a new perspective for robust counterpart optimization.
URI: http://hdl.handle.net/10397/62202
ISSN: 0098-1354
DOI: 10.1016/j.compchemeng.2016.07.022
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