Genetic algorithms in agent-based manufacturing scheduling systems

Abstract

Manufacturing scheduling is the process of selecting from alternative plans and assigning manufacturing resources and time to the set of manufacturing processes in the plan. It is an optimization process by which limited manufacturing resources are allocated over time among parallel and sequential activities. This paper presents a new approach by combining genetic algorithms based search and agent-based negotiation for manufacturing scheduling. Since agent-based approaches emphasize on flexibility and responsiveness and genetic algorithms pursue the optimality of solutions, a combination of agent-based approaches and genetic algorithms provides a promising way to enhance the performance of manufacturing scheduling systems. After a brief research literature review, the paper introduces the proposed integration approach and describes the methods and algorithms for implementing a genetic algorithm in an agent-based manufacturing scheduling system. Some experimental results are also presented.