改进PSO的多目标约束项目进度计划问题研究

Study on Multi-mode Resource-constrained Project Scheduling Problem Based on Particle Swarm Optimization

在项目进度计划问题的研究中,为实现在多执行模式和多资源约束条件下,对项目活动的执行顺序和执行模式进行合理安排的目标,以使项目工期最短,建立了多目标进度计划的目标函数,确定了约束条件。结合微粒群算法求解该组合优化问题,并通过对标准微粒群算法的改进,引入了交换子和交换序的概念,提高了算法的寻优速度和寻优能力,并结合具体的实例验证了改进算法的有效性。

During the research of project scheduling problem, in order to achieve objective that included arranging the execution sequence of the activities and the execution mode reasonably, minimizing the project duration, an objective function of multi-objective scheduling was built and restriction conditions were defined. Then considering the specialty of this combinatorial optimization problem, the standard particle swarm optimization algorithm was improved, and a method presented the concepts of swap operator and swap sequence was designed for improving the optimizing speed and capacity of the algorithm. Finally the validity of such method has been proved with an example.