IMPROVED PARTICLE SWARM OPTIMIZATION FOR RESOURCE LEVELING PROBLEM

摘要：

Resource leveling problem is among the top challenges in project management Traditional heuristic methods and exact algorithms based upon enumeration, branch-and-bound, integer programming or dynamic programmings usually face great difficulties for large and complex projects.In this paper, an improved particle swarm optimization (IPSO) algorithm is presented to solve this problem.Firstly, a mapping is created between the feasible schedule and the position of the particle, then the IPSO begin to search the global best and the local best until the stop criteria is satisfied.A case study is presented and a comparison is made between IPSO and some traditional heuristic methods.Results show that the IPSO algorithm is more satisfying than those of the heuristic methods in terms of feasibility and efficiency.Therefore, this method has its practical application value for the resource leveling problem of project management.

关键词： Resource leveling problem Improved particle swarm optimization Project management Heuristic methods Project scheduling Genetic algorithm

作者: JIAN-XUN QI QIANG WANG XIN-ZHI GUO

作者单位: Department of Business Management, North China Electric Power University, Beijing 102206, China

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 896-901

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）