Job-Shop Scheduling Based on Multiagent Evolutionary Algorithm

• Published in: Advances in Natural Computation pp. 925 - 933
• Main Authors: Zhong, Weicai, Liu, Jing, Jiao, Licheng
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Agent Lattice; Applied sciences; Artificial intelligence; Competitive Behavior; Computer science; control theory; systems; Exact sciences and technology; Local Search; Multiagent System; Operational research and scientific management; Operational research. Management science; Optimal Makespan; Scheduling, sequencing; Multiagent system; Genetic algorithm; Evolutionary algorithm; Job shop; Task scheduling; Scheduling; Artificial intelligence; Workload

With the intrinsic properties of job-shop scheduling problems (JSPs) in mind, we integrate the multiagent systems and evolutionary algorithms to form a new algorithm, Multiagent Evolutionary Algorithm for JSPs (MAEA-JSPs). In MAEA-JSPs, all agents live in a latticelike environment. Making use of the...