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A Memetic Multi-objective Immune Algorithm for Reservoir Flood Control Operation

Author

Listed:
  • Yutao Qi

    (Xidian University)

  • Liang Bao

    (Xidian University)

  • Yingying Sun

    (Xidian University)

  • Jungang Luo

    (Xi’an University of Technology)

  • Qiguang Miao

    (Xidian University)

Abstract

Reservoir flood control operation (RFCO) is a challenging optimization problem with multiple conflicting decision goals and interdependent decision variables. With the rapid development of multi-objective optimization techniques in recent years, more and more research efforts have been devoted to optimize the conflicting decision goals in RFCO problems simultaneously. However, most of these research works simply employ some existing multi-objective optimization algorithms for solving RFCO problem, few of them considers the characteristics of the RFCO problem itself. In this work, we consider the complexity of the RFCO problem in both objective space and decision space, and develop an immune inspired memetic algorithm, named M-NNIA2, to solve the multi-objective RFCO problem. In the proposed M-NNIA2, a Pareto dominance based local search operator and a differential evolution inspired local search operator are designed for the RFCO problem to guide the search towards the and along the Pareto set respectively. On the basis of inheriting the good diversity preserving in immune inspired optimization algorithm, M-NNIA2 can obtain a representative set of best trade-off scheduling plans that covers the whole Pareto front of the RFCO problem in the objective space. Experimental studies on benchmark problems and RFCO problem instances have illustrated the superiority of the proposed algorithm.

Suggested Citation

  • Yutao Qi & Liang Bao & Yingying Sun & Jungang Luo & Qiguang Miao, 2016. "A Memetic Multi-objective Immune Algorithm for Reservoir Flood Control Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(9), pages 2957-2977, July.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:9:d:10.1007_s11269-016-1317-7
    DOI: 10.1007/s11269-016-1317-7
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    References listed on IDEAS

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    Cited by:

    1. Mohammad Hadi Afshar & R. Hajiabadi, 2018. "A Novel Parallel Cellular Automata Algorithm for Multi-Objective Reservoir Operation Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(2), pages 785-803, January.
    2. Francesco Macchione & Gianluca De Lorenzo & Pierfranco Costabile & Babak Razdar, 2016. "The Power Function for Representing the Reservoir Rating Curve: Morphological Meaning and Suitability for Dam Breach Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4861-4881, October.
    3. Ming Hu & Guo H. Huang & Wei Sun & Xiaowen Ding & Yongping Li & Bin Fan, 2016. "Optimization and Evaluation of Environmental Operations for Three Gorges Reservoir," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3553-3576, August.

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