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    Hybrid Genetic Algorithm with Simulated Annealing for Resource-Constrained Project Scheduling

    Source: Journal of Management in Engineering:;2015:;Volume ( 031 ):;issue: 005
    Author:
    Önder Halis Bettemir
    ,
    Rifat Sonmez
    DOI: 10.1061/(ASCE)ME.1943-5479.0000323
    Publisher: American Society of Civil Engineers
    Abstract: Resource-constrained project scheduling problem (RCPSP) is a very important optimization problem in construction project management. Despite the importance of the RCPSP in project scheduling and management, commercial project management software provides very limited capabilities for the RCPSP. In this paper, a hybrid strategy based on genetic algorithms, and simulated annealing is presented for the RCPSP. The strategy aims to integrate parallel search ability of genetic algorithms with fine tuning capabilities of the simulated annealing technique to achieve an efficient algorithm for the RCPSP. The proposed strategy was tested using benchmark test problems and best solutions of the state-of-the-art algorithms. A sole genetic algorithm, and seven heuristics of project management software were also included in the computational experiments. Computational results show that the proposed hybrid strategy improves convergence of sole genetic algorithm and provides a competitive alternative for the RCPSP. The computational experiments also reveal the limitations of the project management software for resource-constrained project scheduling.
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      Hybrid Genetic Algorithm with Simulated Annealing for Resource-Constrained Project Scheduling

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    contributor authorÖnder Halis Bettemir
    contributor authorRifat Sonmez
    date accessioned2017-05-08T22:09:01Z
    date available2017-05-08T22:09:01Z
    date copyrightSeptember 2015
    date issued2015
    identifier other34123472.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/72362
    description abstractResource-constrained project scheduling problem (RCPSP) is a very important optimization problem in construction project management. Despite the importance of the RCPSP in project scheduling and management, commercial project management software provides very limited capabilities for the RCPSP. In this paper, a hybrid strategy based on genetic algorithms, and simulated annealing is presented for the RCPSP. The strategy aims to integrate parallel search ability of genetic algorithms with fine tuning capabilities of the simulated annealing technique to achieve an efficient algorithm for the RCPSP. The proposed strategy was tested using benchmark test problems and best solutions of the state-of-the-art algorithms. A sole genetic algorithm, and seven heuristics of project management software were also included in the computational experiments. Computational results show that the proposed hybrid strategy improves convergence of sole genetic algorithm and provides a competitive alternative for the RCPSP. The computational experiments also reveal the limitations of the project management software for resource-constrained project scheduling.
    publisherAmerican Society of Civil Engineers
    titleHybrid Genetic Algorithm with Simulated Annealing for Resource-Constrained Project Scheduling
    typeJournal Paper
    journal volume31
    journal issue5
    journal titleJournal of Management in Engineering
    identifier doi10.1061/(ASCE)ME.1943-5479.0000323
    treeJournal of Management in Engineering:;2015:;Volume ( 031 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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