Research on Dynamic Scheduling of Job-Shop Production with the Ant Colony Optimal Algorithm

Job-shop dynamic scheduling is an important subject in the fields of production management and combinatorial optimization. It is usually hard to achieve the optimal solution with classical methods due to the high computational complexity of the problem. A solution of job-shop scheduling problem base...

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Veröffentlicht in:Applied Mechanics and Materials Jg. 10-12; S. 109 - 113
Hauptverfasser: Xiong, J., Sun, B.M., Liu, Yong Xian
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Zurich Trans Tech Publications Ltd 01.01.2008
Schlagworte:
Path
NP-Hard (Nondeterministic Polynomial Time-Hard)
Particle Swarm Optimization Algorithm (PSO)
ACO (Ant Colony Optimal Algorithm)
Dynamic Scheduling of Job-Shop Production
ISBN:9780878494705, 0878494707
ISSN:1660-9336, 1662-7482, 1662-7482
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Abstract Job-shop dynamic scheduling is an important subject in the fields of production management and combinatorial optimization. It is usually hard to achieve the optimal solution with classical methods due to the high computational complexity of the problem. A solution of job-shop scheduling problem based on multi-agent is presented for the comparability between the dynamic scheduling problem of job-shop production and the TSP problem. The dynamic scheduling of job-shop production is designed according to the pattern of TSP problem which can be applied with ACO. By the application case, the ACO is the new method to solve the dynamic scheduling of job-shop production.
AbstractList Job-shop dynamic scheduling is an important subject in the fields of production management and combinatorial optimization. It is usually hard to achieve the optimal solution with classical methods due to the high computational complexity of the problem. A solution of job-shop scheduling problem based on multi-agent is presented for the comparability between the dynamic scheduling problem of job-shop production and the TSP problem. The dynamic scheduling of job-shop production is designed according to the pattern of TSP problem which can be applied with ACO. By the application case, the ACO is the new method to solve the dynamic scheduling of job-shop production.
Job-shop dynamic scheduling is an important subject in the fields of production management and combinatorial optimization. It is usually hard to achieve the optimal solution with classical methods due to the high computational complexity of the problem. A solution of job-shop scheduling problem based on multi-agent is presented for the comparability between the dynamic scheduling problem of job-shop production and the TSP problem. The dynamic scheduling of job-shop production is designed according to the pattern of TSP problem which can be applied with ACO. By the application case, the ACO is the new method to solve the dynamic scheduling of job-shop production.
Author Sun, B.M.
Xiong, J.
Liu, Yong Xian
Author_xml – givenname: J.
  surname: Xiong
  fullname: Xiong, J.
  organization: Northeastern University : School of Mechanical Engineering and Automation
– givenname: B.M.
  surname: Sun
  fullname: Sun, B.M.
  organization: Shenyang Motor Factory
– givenname: Yong Xian
  surname: Liu
  fullname: Liu, Yong Xian
  email: yxliu@mail.neu.edu.cn
  organization: Northeastern University : School of Mechanical Engineering and Automation
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NP-Hard (Nondeterministic Polynomial Time-Hard)
Particle Swarm Optimization Algorithm (PSO)
ACO (Ant Colony Optimal Algorithm)
Dynamic Scheduling of Job-Shop Production
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Notes Selected, peer reviewed papers from the 6th International Conference on e-Engineering & Digital Enterprise Technology, August 26-29, 2007, Harbin, China
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