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A genetic algorithm for planning coal purchase of a real electric power plant

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Fuzzy Logic, Neural Networks, and Evolutionary Computation (WWW 1995)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1152))

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Abstract

In this paper, we focus on coal purchase planning in a real electric power plant. Several complex constraints as well as multiple objectives are involved in the planning problem. The conventional integer programming approach is not suitable for this problem because of its complexity. The versatility of genetic algorithms is exemplified through solving the planning problem. Compared to a simple random search and a simulated annealing, the advantages of a genetic algorithm are shown by numerical simulations.

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References

  1. Inuiguchi, M., Ichihashi, H., Tanaka, H.: Fuzzy programming: a survey of recent developments, in: Słowinski, R., Teghem, J. (eds.): Stochastic versus Fuzzy Approaches to Multiobjective Programming under Uncertainty, Kluwer Academic Publishers, Dordrecht (1990) pp. 45–68

    Google Scholar 

  2. Sakawa, M. Fuzzy Sets and Interactive Multiobjective Optimization, Plenum Press, New York and London (1993)

    Google Scholar 

  3. Goldberg, D. E. Genetic Algorithms in Search, Optimization & Machine Learning. Addison-Wesley, Reading, Massachusetts (1983)

    Google Scholar 

  4. Michalewicz, Z. Genetic Algorithms + Data Structure=Evolution Programs, Second extended edition. Springer-Verlag, Berlin (1994)

    Google Scholar 

  5. Hanai, H.: Application of linear programming to material purchase, Communications of the Operations Research Society of Japan, 31 (1986) pp. 360–364 (in Japanese)

    Google Scholar 

  6. Fukumura, S., Sanou, K., Yamakawa, H.: Expert systems for a shipping plan of steel materials and the branch and bound method, Communications of the Operations Research Society of Japan, 33 (1988) pp. 33–39 (in Japanese)

    Google Scholar 

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Authors and Affiliations

  1. Hiroshima University, 4-1, Kagamiyama 1-chome, 739, Higashi-Hiroshima, Japan

    Masahiro Inuiguchi, Tadahiro Miyake & Masatoshi Sakawa

  2. The Chugoku Electric Power Co. Inc., 4-33, Komachi, Naka-ku, 730-91, Hiroshima, Japan

    Isao Shiromaru

Authors
  1. Masahiro Inuiguchi
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  2. Tadahiro Miyake
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  3. Masatoshi Sakawa
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  4. Isao Shiromaru
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Takeshi Furuhashi Yoshiki Uchikawa

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© 1996 Springer-Verlag Berlin Heidelberg

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Inuiguchi, M., Miyake, T., Sakawa, M., Shiromaru, I. (1996). A genetic algorithm for planning coal purchase of a real electric power plant. In: Furuhashi, T., Uchikawa, Y. (eds) Fuzzy Logic, Neural Networks, and Evolutionary Computation. WWW 1995. Lecture Notes in Computer Science, vol 1152. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61988-7_23

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  • DOI: https://doi.org/10.1007/3-540-61988-7_23

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61988-8

  • Online ISBN: 978-3-540-49581-9

  • eBook Packages: Springer Book Archive

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