Abstract
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 designed behaviors, MAEA-JSPs realizes the ability of agents to sense and act on the environment in which they live. During the process of interacting with the environment and the other agents, each agent increases energy as much as possible, so that MAEA-JSPs can find the optima. In the experiments, 59 benchmark JSPs are used, and good performance is obtained.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jain, S., Meeran, S.: Deterministic job-shop scheduling: past, present and future. European Journal of Operational Research 113, 390–434 (1999)
Ferber, J.: Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. Addison-Wesley, New York (1999)
Liu, J.: Autonomous Agents and Multi-Agent Systems: Explorations in Learning, Self-Organization, and Adaptive Computation. World Scientific, Singapore (2001)
Liu, J., Tang, Y.Y., Cao, Y.C.: An evolutionary autonomous agents approach to image feature extraction. IEEE Trans. Evol. Comput. 1(2), 141–158 (1997)
Liu, J., Jing, H., Tang, Y.Y.: Multi-agent oriented constraint satisfaction. Artif. Intell. 136(1), 101–144 (2002)
Zhong, W., Liu, J., Xue, M., Jiao, L.: A multiagent genetic algorithm for global numerical optimization. IEEE Trans. Syst., Man, and Cybern. B 34(2), 1128–1141 (2004)
Fisher, G., Thompson, L.: Probabilistic learning combinations of local job-shop scheduling rules. In: Industrial Scheduling, pp. 225–251. Prentice-Hall, Englewood Cliffs (1963)
Lawrence, S.: Resource constrained project scheduling: An experimental investigation of heuristic scheduling techniques (Supplement). In: Graduate School Ind. Adm., Carnegie-Mellon Univ., Pittsburg, PA (1984)
Applegate, D., Cook, W.: A computational study of the job-shop scheduling problem. ORSA Journal on Computing 3(2), 149–156 (1991)
Wang, L.: Shop Scheduling with Genetic algorithms. Tsinghua University Press, Beijing (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhong, W., Liu, J., Jiao, L. (2005). Job-Shop Scheduling Based on Multiagent Evolutionary Algorithm. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3612. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539902_114
Download citation
DOI: https://doi.org/10.1007/11539902_114
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28320-1
Online ISBN: 978-3-540-31863-7
eBook Packages: Computer ScienceComputer Science (R0)