孙晓雅, 林焰. 人工蜂群算法求解任务可拆分项目调度问题[J]. 微电子学与计算机, 2011, 28(11): 53-56,60.
引用本文: 孙晓雅, 林焰. 人工蜂群算法求解任务可拆分项目调度问题[J]. 微电子学与计算机, 2011, 28(11): 53-56,60.
SUN Xiao-ya, LIN Yan. Artificial Bee Colony Algorithm for Resource-Constrained Project Scheduling Problem with Activity Splitting[J]. Microelectronics & Computer, 2011, 28(11): 53-56,60.
Citation: SUN Xiao-ya, LIN Yan. Artificial Bee Colony Algorithm for Resource-Constrained Project Scheduling Problem with Activity Splitting[J]. Microelectronics & Computer, 2011, 28(11): 53-56,60.

人工蜂群算法求解任务可拆分项目调度问题

Artificial Bee Colony Algorithm for Resource-Constrained Project Scheduling Problem with Activity Splitting

  • 摘要: 针对任务可拆分的资源受限的项目调度问题,提出了一种人工蜂群算法与任务可拆分的串行调度机制相结合的优化方法.人工蜂群算法中每个食物源的位置代表一组项目任务的优先权序列,优先权序列通过调度生成机制转换为可行调度方案,迭代中由三种人工蜂执行不同的操作来实现全局最优解的更新.实算表明,基于优先权的人工蜂群算法可以有效求解任务可拆分项目调度问题,收敛速度较快且精度较高.

     

    Abstract: To solve the resource-constrained project scheduling problem (RCPSP) with activity splitting,an optimization method combined artificial bee colony algorithm with serial scheduling scheme for activity splitting is presented.In ABC algorithm the location of each food source represents priorities of activities,which can be transformed to a feasible schedule by serial scheduling scheme for activity splitting.In the iterative process the global optimal solution is updated according to the different behaviors of three type artificial bees.The actual calculation shows that the artificial bee colony algorithm is valid for resource-constrained and activity splitting project scheduling problem with fast convergence speed and high precision.

     

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