An Enhanced Invasive Weed Optimization in Resource-Constrained Project Scheduling Problem

Abstract

In this research, an enhanced invasive weed optimization (EIWO) has been proposed to solve resource-constrained project scheduling problem (RCPSP) which subjects to the makespan minimization. Firstly, a hybrid population initialization method is illustrated to improve the quality of initial solutions. Secondly, to enhance the local exploitation ability, a local search approach is embedded in the spatial dispersal process. Thirdly, an improved competitive exclusion based on acceptance probability is proposed. At the end of this article, EIWO is tested and verified by standard benchmark problems from PSPLIB. Compared with the existing algorithms through computer numerical experiments, the new EIWO algorithm is more effective and efficient in solving RCPSP.