A TOPSIS-BASED ENTROPIC REGULARIZATION APPROACH FOR SOLVING FUZZY MULTI-OBJECTIVE NONLINEAR PROGRAMMING PROBLEMS

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概要

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• In this work, a version of the technique for order preference by similarity ideal solution (TOPSIS) with entropic regularization approach is developed for solving the fuzzy multi-objective nonlinear programming (MONLP) problems. Applying the basic principle of compromise of TOPSIS, the fuzzy MONLP problem can be reduced into a fuzzy bi-objective nonlinear programming problem. Moreover, following the "tolerance approach," the solution of the fuzzy bi-objective nonlinear programming problem can be obtained by solving a min-max problem. An entropic regularization approach is then applied for solving such a problem. Computational results are provided to illustrate the validity and efficiency of the proposed method.

• 社団法人日本オペレーションズ・リサーチ学会の論文
• 2012-12-00

著者

• Liu Fung-Bao

  I-Shou University

• Hu Cheng-Feng

  Department of Industrial Management I-Shou University

関連論文

• A TOPSIS-BASED ENTROPIC REGULARIZATION APPROACH FOR SOLVING FUZZY MULTI-OBJECTIVE NONLINEAR PROGRAMMING PROBLEMS

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