工业工程

工业工程 ›› 2012, Vol. 15 ›› Issue (3): 57-61.

• 专题论述 • 上一篇    下一篇

基于混沌粒子群的资源受限项目调度问题

  

  1. 上海理工大学 管理学院，上海 200093
  • 出版日期:2012-06-30 发布日期:2012-07-21
  • 作者简介:谢阳（1988-），男，湖北省人，硕士研究生，主要研究方向为项目管理.
  • 基金资助:

    教育部人文社会科学规划基金资助项目 （10YJA630187)；高等学校博士点基金资助项目 (20093120110008)；上海市重点学科建设资助项目（S30504）；上海研究生创新基金资助项目（JWCXSL1102）；上海市教育委员会科研创新资助项目（12ZS133）

Resource Constrained Project Scheduling Based on Chaos Particle Swam Optimization

  1. School of Management，University of Shanghai for Science and Technology，Shanghai 200093，China
  • Online:2012-06-30 Published:2012-07-21

摘要： 鉴于基本粒子群算法易陷入局部最优，提出一种将混沌算法嵌入基本粒子群的混沌粒子群算法，并将其用于求解典型的资源受限项目调度问题。采用基于优先值的粒子编码方式和串行调度方案，分别用基本粒子群算法和混沌粒子群算法对实例求解。并且比较了2种算法求解多资源受限项目调度问题的性能。结果表明：混沌粒子群算法在距最优值的平均偏差和达到最优值的次数百分比等性能上要优于基本的粒子群算法，并且混沌粒子群具有更好的收敛性。但是，混沌粒子群算法在计算达到最优工期的平均时间上略比基本粒子群算法逊色。

关键词: 混沌, 粒子群算法, 资源受限项目调度

Abstract: The resourceconstrained project scheduling problem is addressed in this paper. As the basic particle swarm optimization (BPSO) method is easy to be trapped in a local optimum, a chaos particle swarm optimization (CPSO) algorithm is proposed. It combines the chaos algorithm with the BPSO and is used to solve the typical multiple resourcesconstrained project scheduling problem. To test the performance of the proposed method, both BPSO and CPSO are used to solve an instance. Comparison shows that CPSO performs better than BPSO in average deviation from the optimum and the percentage of reaching the optimal value, etc. Also, it has better convergence than BPSO. However, in the average time to achieve the optimum, the CPSO is not as good as BPSO.

Key words: chaos, particle swarm optimization (PSO), resourceconstrained project scheduling