Reliability Optimization Design Using Hybrid NN-GA with Fuzzy Logic Controller

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概要

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• In this study, a hybrid genetic algorithm/neural network with fuzzy logic controller (NN-flcGA) is proposed to find the global optimum of reliability assignment/redundant allocation problems which should be simultaneously determined two different types of decision variables. Several researchers have obtained acceptable and satisfactory results using genetic algorithms for optimal reliability assignment/redundant allocation problems during the past decade. For large-size problems, however, genetic algorithms have to enumerate numerous feasible solutions due to the broad continuous search space. Recently, a hybridized GA combined with a neural network technique (NN-hGA) has been proposed to overcome this kind of difficulty. Unfortunately, it requires a high computational cost though NN-hGA leads to a robuster and steadier global optimum irrespective of the various initial conditions of the problems. The efficacy and efficiency of the NN-flcGA is demonstrated by comparing its results with those of other traditional methods in numerical experiments. The essential features of NN-flcGA namely, 1) its combination with a neural network (NN) technique to devise initial values for the GA, 2) its application of the concept of a fuzzy logic controller when tuning strategy GA parameters dynamically, and 3) its incorporation of the revised simplex search method, make it possible not only to improve the quality of solutions but also to reduce computational cost.

• 社団法人電子情報通信学会の論文
• 2002-02-01

著者

• Tsujimura Yasuhiro

  Department Of Computer And Information Engg. Nippon Institute Of Technology

• Gen Mitsuo

  Department Of Industrial And Information Systems Engg. Ashikaga Institute Of Technology

• Gen Mitsuo

  Department Of Industrial & Information Systems Engineering Ashikaga Institute Of Technology

• LEE ChangYoon

  SCM & Logistics Research Center, Hanyang University

• Lee Changyoon

  Scm & Logistics Research Center Hanyang University

• Gen Mitsuo

  Department Of Industrial & Information Systems Engineering

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