A multi-agent genetic algorithm for resource constrained project scheduling problems

Xiaoxiao Yuan, Chuanfu Xiao, Xiyu Lv, Jing Liu

Abstract: A multi-agent genetic algorithm is proposed to solve single-mode resource constrained project scheduling problems (MAGA-RCPSPs). In MAGA-RCPSPs, an agent represents a candidate solution to the RCPSP, and all agents live in a latticelike environment, with each agent fixed on a lattice point. In the experiments, benchmark problems Patterson and J30 are used. The results show that MAGA-RCPSPs has a good performance.