Intelligent Job Shop Scheduling Based on MAS and Integrated Routing Wasp Algorithm and Scheduling Wasp Algorithm

Abstract

Dynamic scheduling algorithms are gaining more and more special attention for their satisfying robustness when confronted with unexpected events as well as their considerably high performance in scheduling. An organization structure for intelligent job shop scheduling based on MAS (Multiple Agents System) is put forward to achieve effective and efficient production. A hybrid multilayer agent structure is put forward to facilitate constructing various agents. Consequently, all resources in a manufacturing system are reorganized into an agile manufacturing network of agents of autonomous and cooperative characteristics. Regarding wasps as a specific kind of agents, wasp colony algorithms are used to solve job shop dynamic scheduling problem. Based on the principle of the wasp colony algorithm, two different algorithms, namely the routing wasp algorithm and the scheduling wasp algorithm, are combined to solve the job shop dynamic scheduling problem. The algorithms are modified to better adapt to job shop dynamic scheduling environment. The algorithms are developed based on Eclipse 3.2 and J2SE 6.0. Simulation experiments are accomplished and experimental data are analyzed. The results show that the principle of the algorithms is simple, their computational quantity is small, and they can be applied to multi-batch dynamic scheduling with unpredictable entry time due to their favorable potential.