• DocumentCode
    724440
  • Title

    The multi-objective water resources optimization scheduling based on chaos genetic algorithm

  • Author

    Zhao Xiao-qiang ; He Zhi-e

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Technol., Lanzhou, China
  • fYear
    2015
  • fDate
    23-25 May 2015
  • Firstpage
    4500
  • Lastpage
    4505
  • Abstract
    Scheduling of water resources is the rational utilization of water resources and the main way and effective means to solve the shortage of water resources, it has some characteristics of more users, more water, multi-level and multi-objective. Chaos genetic algorithm (CGA) can be solved in the process of water resources scheduling problem such as slow convergence speed, easy to fall into local optimization, but there are some limitations in the practical application. In this paper, by using multi-objective decision scheduling, real-time and regularity of rainfall will be combined with chaos genetic algorithm (GA), a more reasonable adjustment of water supply, water resources allocation optimization. The simulation results show that multi-objective decision-making based on chaos genetic algorithm can better satisfy user needs, stick to the waste water, improve the satisfaction degree of the water, more comprehensive benefits.
  • Keywords
    convergence; decision making; genetic algorithms; scheduling; water resources; water supply; CGA; chaos genetic algorithm; convergence speed; local optimization; multiobjective decision scheduling; multiobjective decision-making; multiobjective water resource optimization scheduling; water resource allocation optimization; water resource scheduling problem; water resource utilization; water supply; Chaos; Genetic algorithms; Job shop scheduling; Logistics; Optimization; Water resources; CGA; multi-objective decision; scheduling model; water resources optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2015 27th Chinese
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-1-4799-7016-2
  • Type

    conf

  • DOI
    10.1109/CCDC.2015.7162718
  • Filename
    7162718