人工蜂群算法求解资源受限项目调度问题

针对资源受限项目调度问题,提出了一种基于人工蜂群算法的优化方法。人工蜂群算法中每个食物源的位置代表一种项目任务的优先权序列,每个食物源的位置通过扩展串行调度机制转换成可行的调度方案,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。实验结果表明,人工蜂群算法是求解资源受限项目调度问题的有效方法,同时扩展调度机制的引入可以加速迭代收敛的进程。

Artificial bee colony algorithm for resource-constrained project scheduling problem

To solve the resource-constrained project scheduling problem （RCPSP）, an optimization algorithm called artifical bee colony （ABC） is presented. In ABC algorithm the location of each food source represents priorities of activities, which can be transformed to a feasible schedule by the extended serial scheduling scheme. 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 ABC algorithm is valid for RCPSP. It also shows that extended scheduling scheme can accelerate the convergence process obviously.