Solving Resource Constrained Multiple Project Scheduling Problems by Random Key-Based Genetic Algorithm

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  • Okada Ikutaro
    Kinki University, Department of Management and Communication
  • Lin Lin
    Waseda University, Graduate school of Information, Production and systems
  • Gen Mitsuo
    Waseda University, Graduate school of Information, Production and systems

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  • ランダムキー型遺伝的アルゴリズムによる資源制約付き多重プロジェクト・スケジューリング問題の解法
  • ランダム キーガタ イデンテキ アルゴリズム ニ ヨル シゲン セイヤク ツキ タジュウ プロジェクト スケジューリング モンダイ ノ カイホウ

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Abstract

In this paper, we propose a hybrid genetic algorithm with fuzzy logic controller (flc-rkGA) to solve the resource-constrained multiple project scheduling problem (rc-mPSP) which is well known one of NP-hard problems and the objective in this paper is to minimize total complete time in the project. It is difficult for treating the rc-mPSP problems with traditional optimization techniques. The new approach proposed is based on the hybrid genetic algorithm (flc-rkGA) with fuzzy logic controller (FLC) and the random-key encoding. For these rc-mPSP problems, we demonstrate that the proposed flc-rkGA to solve the rc-mPSP problem yields better results than several heuristic genetic algorithms presented in the computation result.

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