Agent-based distributed scheduling for virtual job shops

Nowadays, market globalisation and stiff world-wide competition require flexible, demand-driven, and reconfigurable production systems that can adapt to the requirements of the increasing reduction in product life cycle and rapid changes in market demand. The advent and development of network technology (especially the Internet) and distributed computing technology make it possible for geographically dispersed manufacturing resources to be integrated and deployed effectively and efficiently. In addition, manufacturing enterprises can expand their throughput within a short time and rapidly reduce the production cycle via transferring certain jobs to other available manufacturing resources in the globalised manufacturing environment, viz., manufacturing enterprises can expand their throughput through the dynamic formation of virtual job shops according to the production requirements. Owing to more open manufacturing environments and rapid changes of market demands, the traditional centralised scheduling approaches are not suitable for this open distributed manufacturing environment. This paper proposes a distributed scheduling approach in which a multi-agent solution towards a ‘task-machine’ assignment is presented. The main points of discussion are the formation of a virtual job shop that is based on market mechanism and the distributed scheduling approach based on negotiation.

[1]  Procurement Bidding in First-Price and Second-Price, Sealed-Bid Auctions within the Common-Value Paradigm , 2002 .

[2]  J. Christopher Beck,et al.  Constraint-directed techniques for scheduling alternative activities , 2000, Artif. Intell..

[3]  Miguel A. Salido,et al.  Heuristic Methods for Solving Job-Shop Scheduling Problems , 2000, PuK.

[4]  Carlos Ramos,et al.  The Fabricare system: a multi-agent-based scheduling prototype , 2004 .

[5]  Manfredi Bruccoleri,et al.  Distributed intelligent control of exceptions in reconfigurable manufacturing systems , 2003 .

[6]  George Q. Huang,et al.  Agent-based modeling of supply chains for distributed scheduling , 2006, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[7]  Andrew Y. C. Nee,et al.  Web-based Multi-functional Scheduling System for a Distributed Manufacturing Environment , 2002, Concurr. Eng. Res. Appl..

[8]  H. V. Parunak Chapter 10 – Manufacturing Experience with the Contract Net , 1987 .

[9]  Weiming Shen,et al.  A Hybrid Agent-Oriented Infrastructure for Modeling Manufacturing Enterprises , 1998 .

[10]  Albert D. Baker,et al.  Manufacturing control with a market-driven contract net , 1992 .

[11]  Michael J. Shaw,et al.  Dynamic scheduling in cellular manufacturing systems: A framework for networked decision making , 1988 .

[12]  James J. Solberg,et al.  INTEGRATED SHOP FLOOR CONTROL USING AUTONOMOUS AGENTS , 1992 .

[13]  Michael Pinedo,et al.  Scheduling: Theory, Algorithms, and Systems , 1994 .

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

[15]  Robert W. Brennan,et al.  Holonic job shop scheduling using a multiagent system , 2005, IEEE Intelligent Systems.

[16]  Sergey Kornienko,et al.  Application of multi-agent planning to the assignment problem , 2004, Comput. Ind..

[17]  J. Christopher Beck,et al.  This Is a Publication of The American Association for Artificial Intelligence , 2022 .

[18]  Mark S. Fox,et al.  Intelligent Scheduling , 1998 .

[19]  Weiming Shen,et al.  Distributed Manufacturing Scheduling Using Intelligent Agents , 2002, IEEE Intell. Syst..

[20]  Angelo Oddi,et al.  IPSS: A Hybrid Approach to Planning and Scheduling Integration , 2006, IEEE Transactions on Knowledge and Data Engineering.

[21]  R. McAfee,et al.  Auctions and Bidding , 1986 .

[22]  P. Klemperer Auction Theory: A Guide to the Literature , 1999 .

[23]  Yi-Chi Wang,et al.  Judging the value of additional information on the performance of intelligent agents in manufacturing control , 2000, SPIE Optics East.

[24]  Américo Azevedo,et al.  An advanced agent-based order planning system for dynamic networked enterprises , 2004 .

[25]  Norman M. Sadeh,et al.  Resource allocation in distributed factory scheduling , 1991, IEEE Expert.

[26]  Harry M. Sneed Encapsulation of legacy software: A technique for reusing legacy software components , 2000, Ann. Softw. Eng..

[27]  Weiming Shen,et al.  MetaMorph II: an agent-based architecture for distributed intelligent design and manufacturing , 2000, J. Intell. Manuf..

[28]  Gautam Biswas,et al.  Performance Evaluation of Contract Net-Based Heterarchical Scheduling for Flexible Manufacturing Systems , 1997, Intell. Autom. Soft Comput..

[29]  C. Ramos,et al.  Manufacturing Entities with Incomplete Information , 2000 .

[30]  Peter B. Luh,et al.  Lagrangian relaxation neural networks for job shop scheduling , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[31]  H. Van Dyke Parunak,et al.  The AARIA agent architecture: From manufacturing requirements to agent-based system design , 2001, Integr. Comput. Aided Eng..

[32]  Katsuhiko Takahashi,et al.  Simulated annealing approach for minimizing the makespan of the general job-shop , 1999 .

[33]  Pierre Massotte,et al.  Comparison of negotiation protocols in dynamic agent-based manufacturing systems , 2006 .

[34]  Keith Schmidt Using Tabu Search to Solve the Job Shop Scheduling Problem with Sequence Dependent Setup Times , 2001 .

[35]  Duncan McFarlane,et al.  Adaptive agent-based manufacturing control and its application to flow shop routing control , 2004 .

[36]  Arndt Lüder,et al.  Distributed intelligence for plant automation based on multi-agent systems: the PABADIS approach , 2004 .

[37]  Peter Ross,et al.  A Promising Genetic Algorithm Approach to Job-Shop SchedulingRe-Schedulingand Open-Shop Scheduling Problems , 1993, ICGA.