A Multi-agent Social Evolutionary Algorithm for Resource-Constrained Project Scheduling

With the intrinsic properties of the Resource-Constrained Project Scheduling Problem(RCPSP) in mind, we integrate the multi-agent systems, social acquaintance net and evolutionary algorithms to form a new algorithm, a multi-agent social evolutionary algorithm for resource-constrained project scheduling problem (MASEA-RCPSP). In this algorithm, all agents live in lattice-like environment. Making use of the designed behaviors, MASEA-RCPSP realizes the ability of agents to sense and act on the environment in which they live, and the local environments of all the agents are constructed by social acquaintance net. During the process of interacting with the environment and the other agents, each agent increases energy as much as possible, so that MASEA-RCPSP can find the optima. In the experiments, 2040 benchmark PSPLIB are used, and good performance is obtained.