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Hybrid Particle Swarm and Differential Evolution Algorithm for Solving Multimode Resource-Constrained Project Scheduling Problem

机译:求解混合模式资源受限项目调度问题的混合粒子群与差分进化算法

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In order to find a feasible solution for the multimode resource-constrained project scheduling problem (MRCPSP), a hybrid of particle swarm optimization (PSO) and differential evolution (DE) algorithm is proposed in this paper. The proposed algorithm uses a two-level coding structure. The upper-level structure is coded for scheduling sequence, which is optimized by PSO algorithm. The lower-level structure is coded for project execution mode, and DE algorithm is used to solve the optimal scheduling model. The effectiveness and advantages of the proposed algorithm are illustrated by using the test function of project scheduling problem library (PSPLIB) and comparing with other scheduling methods. The results show that the proposed algorithm can well solve MRCPSP.
机译:为了找到解决多模式资源受限项目调度问题(MRCPSP)的可行方案,提出了粒子群算法(PSO)和差分进化算法(DE)的混合算法。所提出的算法使用两级编码结构。上层结构被编码用于调度序列,该序列通过PSO算法进行了优化。底层结构被编码为项目执行模式,并且使用DE算法来求解最佳调度模型。通过使用项目调度问题库(PSPLIB)的测试功能并与其他调度方法进行比较,说明了该算法的有效性和优势。结果表明,该算法能够很好地解决MRCPSP问题。

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  • 来源
    《Journal of control science and engineering》 |2015年第2015期|923791.1-923791.6|共6页
  • 作者单位

    Guangxi Key Laboratory of New Energy and Building Energy Saving, Guilin University of Technology, Guilin 541004, China,College of Mechanical and Control Engineering, Guilin University of Technology, Guilin 541004, China;

    College of Information Science and Engineering, Guilin University of Technology, Guilin 541004, China;

    Guangxi Key Laboratory of New Energy and Building Energy Saving, Guilin University of Technology, Guilin 541004, China,College of Mechanical and Control Engineering, Guilin University of Technology, Guilin 541004, China;

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