Dynamic flexible job shop scheduling with alternative process plans: an agent-based approach

This paper studies a flexible job shop problem considering dynamic events such as stochastic job arrivals, uncertain processing times, and unexpected machine breakdowns. Also, the considered job shop problem has routing flexibility and process flexibility. A multi-agent scheduling system has been developed for solution with good quality and robustness. A pheromone-based approach is proposed for coordination among agents. The proposed multi-agent approach is compared with five dispatching rules from literature via simulation experiments to statistical analysis. The simulation experiments are performed under various experimental settings such as shop utilization level, due date tightness, breakdown level, and mean time to repair. The results show that the proposed agent-based approach performs well under all problem settings.

[1]  Yoke San Wong,et al.  Machine Selection Rules in a Dynamic Job Shop , 2000 .

[2]  Yong Liu,et al.  Dynamic Scheduling Method Based on Combination of Contract Net with Mediator , 2005, 2005 International Conference on Machine Learning and Cybernetics.

[3]  Jesuk Ko,et al.  A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling , 2003, Comput. Oper. Res..

[4]  Haruhiko Suwa,et al.  Capability of cumulative delay based reactive scheduling for job shops with machine breakdowns , 2007, Comput. Ind. Eng..

[5]  H. L. Ong,et al.  Metaheuristics for minimizing the makespan of the dynamic shop scheduling problem , 2004, Adv. Eng. Softw..

[6]  Ihsan Sabuncuoglu,et al.  Analysis of reactive scheduling problems in a job shop environment , 2000, Eur. J. Oper. Res..

[7]  Hendrik Van Brussel,et al.  Pheromone based emergent shop floor control system for flexible flow shops , 1999, Artif. Intell. Eng..

[8]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[9]  Liang Gao,et al.  Integration of process planning and scheduling - A modified genetic algorithm-based approach , 2009, Comput. Oper. Res..

[10]  Massimo Paolucci,et al.  A multi-agent system for dynamic just-in-time manufacturing production scheduling , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[11]  Kai Kang,et al.  MAS Equipped with Ant Colony Applied into Dynamic Job Shop Scheduling , 2007, ICIC.

[12]  W. Xiang,et al.  Ant colony intelligence in multi-agent dynamic manufacturing scheduling , 2008, Eng. Appl. Artif. Intell..

[13]  V. Vinod,et al.  Scheduling a dynamic job shop production system with sequence-dependent setups: An experimental study , 2008 .

[14]  Ana Madureira,et al.  Developing a Multi-Agent System for Dynamic Scheduling Trough Aose Perspective , 2007 .

[15]  Douglas H. Norrie,et al.  Agent-Based Systems for Intelligent Manufacturing: A State-of-the-Art Survey , 1999, Knowledge and Information Systems.

[16]  C. Ramos,et al.  Cooperation Mechanism for Team-Work based Multi-Agent System in Dynamic Scheduling through Meta-Heuristics , 2007, 2007 IEEE International Symposium on Assembly and Manufacturing.

[17]  Andrew Y. C. Nee,et al.  Performance of an ant colony optimisation algorithm in dynamic job shop scheduling problems , 2009 .

[18]  Jie Wu,et al.  Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence, 4th International Conference on Intelligent Computing, ICIC 2008, Shanghai, China, September 15-18, 2008, Proceedings , 2008, ICIC.

[19]  Weiming Shen,et al.  Applications of agent-based systems in intelligent manufacturing: An updated review , 2006, Adv. Eng. Informatics.

[20]  B. Karimi,et al.  New dispatching rules to minimize rejection and tardiness costs in a dynamic flexible flow shop , 2009 .

[21]  C. Bierwirth,et al.  Genetic algorithm based scheduling in a dynamic manufacturing environment , 1995, Proceedings of 1995 IEEE International Conference on Evolutionary Computation.

[22]  Bala Ram,et al.  Bio-inspired scheduling for dynamic job shops with flexible routing and sequence-dependent setups , 2006 .

[23]  Donglai Li,et al.  Contract Net based Scheduling Approach using Interactive Bidding for Dynamic Job Shop Scheduling , 2007, 2007 IEEE International Conference on Integration Technology.

[24]  Edmund H. Durfee,et al.  Distributed Problem Solving and Planning , 2001, EASSS.

[25]  Oliver Holthaus,et al.  Scheduling in job shops with machine breakdowns: an experimental study , 1999 .

[26]  Chandrasekharan Rajendran,et al.  A comparative study of dispatching rules in dynamic flowshops and jobshops , 1999, Eur. J. Oper. Res..

[27]  Michael J. Shaw,et al.  Information-Based Dynamic Manufacturing System Scheduling , 2001 .

[28]  Weiming Shen,et al.  Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[29]  Guochuan Zhang,et al.  A note on on-line scheduling with partial information , 2002 .

[30]  Chandrasekharan Rajendran,et al.  Scheduling in dynamic assembly job-shops to minimize the sum of weighted earliness, weighted tardiness and weighted flowtime of jobs , 2005, Comput. Ind. Eng..