Improved Particle Swarm Optimization for Resource Leveling Problem

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.