Robust-Soft Solutions in Linear Optimization Problems with Fuzzy Parameters

Masahiro Inuiguchi ()
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Masahiro Inuiguchi: Osaka University

Chapter Chapter 8 in Robustness Analysis in Decision Aiding, Optimization, and Analytics, 2016, pp 171-190 from Springer

Abstract: Abstract Linear optimization linear programming problems with fuzzy parameters were studied deeply and widely. Many of the approaches to fuzzy problems generate robust solutions. However, they were based on satisficing approaches so that the solutions do not maintain the optimality or suboptimality against the fluctuations in the coefficients. In this chapter, we describe a robust solution maintaining the suboptimality against the fluctuations in the coefficients. We formulate the problem as an extension of the minimax regret/maximin achievement rate problem and investigate a solution procedure based on a bisection method and a relaxation method. It is shown that the proposed solution procedure is created well so that both bisection and relaxation methods converge simultaneously.

Keywords: Satisficing Approach; Linear Programming Problem; Fuzzy Objective Function Value; Strict Uncertainty; Objective Coefficient Vector (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-319-33121-8_8

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DOI: 10.1007/978-3-319-33121-8_8

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