• Login
    Search 
    •   DORA Home
    • Search
    •   DORA Home
    • Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Search

    Show Advanced FiltersHide Advanced Filters

    Filters

    Use filters to refine the search results.

    Now showing items 1-2 of 2

    • Sort Options:
    • Relevance
    • Title Asc
    • Title Desc
    • Issue Date Asc
    • Issue Date Desc
    • Results Per Page:
    • 5
    • 10
    • 20
    • 40
    • 60
    • 80
    • 100
    Thumbnail

    Genetic algorithm and neural network hybrid approach for job-shop scheduling 

    Zhao, Kai; Yang, Shengxiang; Wang, Dingwei (ACTA Press, 1998)
    This paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal ...
    Thumbnail

    A neural network and heuristics hybrid strategy for job-shop scheduling problem 

    Yang, Shengxiang; Wang, Dingwei (1999-06)
    A new efficient neural network and heuristics hybrid strategy for job-shop scheduling is presented. The neural network has the property of adapting its connection weights and biases of neural units while solving feasible ...
    Feed iconrss
    Bookmark icon Bookmark Search

    Submission Guide | Reporting Guide | Reporting Tool | DMU Open Access Libguide | Take Down Policy | Connect with DORA
    DMU LIbrary
     

     

    Browse

    All of DORACommunities & CollectionsAuthorsTitlesSubjects/KeywordsResearch InstituteBy Publication DateBy Submission Date

    My Account

    Login

    Discover

    AuthorWang, Dingwei (2)
    Yang, Shengxiang (2)
    Zhao, Kai (1)SubjectJob-shop scheduling (2)
    Neural network (2)
    Constraint satisfaction (1)Genetic algorithm (1)Heuristics (1)Hybrid strategy (1)... View MoreDate Issued1998 (1)1999 (1)Has File(s)Yes (2)

    Submission Guide | Reporting Guide | Reporting Tool | DMU Open Access Libguide | Take Down Policy | Connect with DORA
    DMU LIbrary