• DocumentCode
    3289278
  • Title

    Application Job-Shop Scheduling Problems Based on Improved Genetic Algorithm to Engineering Equipment´s Rush-Repair in Battlefield

  • Author

    Zhang, Qiyi ; Wang, Wentao

  • Author_Institution
    Automobile Manage. Inst. of PLA, Bengbu, China
  • fYear
    2009
  • fDate
    16-17 May 2009
  • Firstpage
    314
  • Lastpage
    317
  • Abstract
    Engineering equipmentpsilas rush repairs in battlefield optimal assignment model was established. Combining the features of job shop scheduling problems, described the complexity of this problem. In order to find global optimal results efficiently, traditional GAs were improved and used for study of this problem. Though genetic algorithm, as an effective global search method, had been used in many engineering problems, it had the disadvantages of slow convergence and poor stability in practical engineering. In order to overcome these problems, an improved genetic algorithm was proposed in terms of creation of the initial population, genetic operators, etc. At the end, the steps to solve the optimal model were put forward. With this model we had obtained ideal results. This shows that the method can offer a scientific and effective support for a decision maker in command automation of the engineering equipmentpsilas rush repairs in battlefield.
  • Keywords
    genetic algorithms; job shop scheduling; maintenance engineering; search problems; battlefield optimal assignment model; command automation; decision maker; engineering equipment; genetic algorithm; job shop scheduling; rush repairs; Automobiles; Automotive engineering; Circuits; Conference management; Electronic mail; Engineering management; Genetic algorithms; Genetic engineering; Programmable logic arrays; Search methods; engineering equipment; genetic algorithm; job-shop scheduling; rush-repairs in battlefield;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits, Communications and Systems, 2009. PACCS '09. Pacific-Asia Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-0-7695-3614-9
  • Type

    conf

  • DOI
    10.1109/PACCS.2009.118
  • Filename
    5232349