A multi-agent architecture for integrated process planning and scheduling with meta-heuristics

Abstract

Manufacturing process planning and production scheduling functions are usually performed sequentially, disregarding the dynamic nature of manufacturing system. Integrated process planning and scheduling (IPPS) is to combine both the process planning and scheduling problems in the consideration, with the aim to improve the flexibility and adaptability of the actual process plan and the schedule in the dynamical manufacturing environment. In this paper, a hybrid approach of MAS and meta-heuristic search algorithm is proposed to solve the IPPS problem. A new MAS architecture is established to cater for the problem domain of IPPS which is to be solved with meta-heuristic algorithms such as genetic algorithm (GA) or ant colony optimization (ACO). The hybrid MAS-based heuristic approach can enhance the solution quality and efficiency of the IPPS solution due to the distributed and concurrent computation of the heuristic search algorithm.