Job-Shop Scheduling Based on Multiagent Evolutionary Algorithm

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...

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Bibliographic Details
Published inAdvances in Natural Computation pp. 925 - 933
Main Authors Zhong, Weicai, Liu, Jing, Jiao, Licheng
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture 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
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Summary: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.
ISBN:9783540283201
354028320X
3540283234
9783540283232
ISSN:0302-9743
1611-3349
DOI:10.1007/11539902_114