Genetic algorithm for supply planning optimization under uncertain demand

Tezuka Masaru, Hiji Masahiro

研究成果: Chapter

5 引用 (Scopus)

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Supply planning optimization is one of the most important issues for manufacturers and distributors. Supply is planned to meet the future demand. Under the uncertainty involved in demand forecasting, profit is maximized and risk is minimized. In order to simulate the uncertainty and evaluate the profit and risk, we introduced Monte Carlo simulation. The fitness function of GA used the statistics of the simulation. The supply planning problems are multi-objective, thus there are several Pareto optimal solutions from high-risk and high-profit to low-risk and low-profit. Those solutions are very helpful as alternatives for decision-makers. For the purpose of providing such alternatives, a multi-objective genetic algorithm was employed. In practice, it is important to obtain good enough solutions in an acceptable time. So as to search the solutions in a short time, we propose Boundary Initialization which initializes population on the boundary of constrained space. The initialization makes the search efficient. The approach was tested on the supply planning data of an electric appliances manufacturer, and has achieved a remarkable result.

元の言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
編集者Erick Cantú-Paz, James A. Foster, Graham Kendall, Mark Harman, Dipankar Dasgupta, Kalyanmoy Deb, Lawrence David Davis, Rajkumar Roy, Una-May O'Reilly, Hans-Georg Beyer, Russell Standish, Stewart Wilson, Joachim Wegener, Mitch A. Potter, Alan C. Schultz, Kathryn A. Dowsland, Natasha Jonoska, Julian Miller
出版者Springer Verlag
ページ2337-2346
ページ数10
ISBN(印刷物)3540406034, 9783540406037
DOI
出版物ステータスPublished - 2003

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2724
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • これを引用

    Masaru, T., & Masahiro, H. (2003). Genetic algorithm for supply planning optimization under uncertain demand. : E. Cantú-Paz, J. A. Foster, G. Kendall, M. Harman, D. Dasgupta, K. Deb, L. David Davis, R. Roy, U-M. O'Reilly, H-G. Beyer, R. Standish, S. Wilson, J. Wegener, M. A. Potter, A. C. Schultz, K. A. Dowsland, N. Jonoska, & J. Miller (版), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 2337-2346). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 2724). Springer Verlag. https://doi.org/10.1007/3-540-45110-2_126