A Hybrid Scatter Search for the Resource-Constrained Project Scheduling Problem


Department of Industrial Engineering,Sharif University of Technology


In this paper we develop a new hybrid metaheuristic algorithm based on the scatter search approach to solve the well-known resource-constrained project scheduling problem. This algorithm combines two solutions from scatter search to build a set of precedence feasible activity lists and select some of them as children for the new population. We use the idea presented in the forward/backward improvement technique to define two types of schedule, direct and reverse, and the members of the sequential populations change alternately between these two types of schedule. Extensive computational tests were performed on standard benchmark datasets and the results are compared with the best available results. Comparative computational tests indicate that our procedure is a very effective metaheuristic algorithm.