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
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- Lin Lin
- Waseda University, Graduate school of Information, Production and systems
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- Gen Mitsuo
- Waseda University, Graduate school of Information, Production and systems
Bibliographic Information
- Other Title
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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.
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 128 (3), 441-449, 2008
The Institute of Electrical Engineers of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390001204604206976
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- NII Article ID
- 10021131770
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 9401095
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed