Agent-based project scheduling

Agent technology offers a new way of thinking about many of the classic problems in operations research. Among these are problems such as project scheduling subject to resources constraints. In this paper, we develop and experimentally evaluate eight agent-based algorithms for solving the multimode, resource-constrained project scheduling problem. Our algorithms differ in the priority rules used to control agent access to resources. We apply our approach to a 51-activity project originally published by Maroto and Tormos. We solve the problem using two types of agent-based systems: (i) a system of simple, reactive agents that we call basic agents; and (ii) a system of more complex, deliberative agents that we call enhanced agents. Of the eight priority rules tested, we find that priority based on shortest processing time performs best in terms of schedule quality when applied by basic agents while the priority based on earliest due date performs best when applied by enhanced agents. In comparing agents across priority rules, we find that enhanced agents generate much better schedules (with makespans up to 66% shorter in some cases) and require only slightly more computation time.