Agents-based interaction protocols and topologies in manufacturing task allocation

The focus of this paper is on interaction protocols and topologies of multi-agent systems for task allocation in manufacturing applications. Resource agents in manufacturing are members of a network whose possible logical topologies and governing interaction protocol influence the scheduling and control in the multi-agent system. Four models are identified in the paper, each having specific rules and characteristics for scheduling and task allocation. The models use either a standard interaction method such as Contract-Net Protocol (CNP), or a different method proposed in this research. A Java-based multi-agent system was developed to simulate different scenarios of task allocation and to compare the four models in terms of performance indicators. Data from an industrial case study involving a manufacturing shop floor was used to evaluate the performance of the models. The results indicate meaningful differences between the four models, and highlight the performance potential of a proposed task allocation model.

[1]  Dongmei Xie,et al.  Consensus of second-order discrete-time multi-agent systems with fixed topology , 2012 .

[2]  Weiming Shen,et al.  Due-Date Management Through Iterative Bidding , 2011, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[3]  Paulo Leitão.  A Bio-Inspired Solution for Manufacturing Control Systems , 2008, BASYS.

[4]  J. Váncza,et al.  Holonic manufacturing with economic rationality , 1998 .

[5]  Patrick Pujo,et al.  Pull control for job shop: holonic manufacturing system approach using multicriteria decision-making , 2012, J. Intell. Manuf..

[6]  Guiovanni Jules,et al.  A holonic systems approach to the formation of manufacturing networks , 2010, 2010 IEEE 9th International Conference on Cyberntic Intelligent Systems.

[7]  Victor R. Lesser,et al.  A Multi-Agent Approach for Peer-to-Peer Based Information Retrieval System , 2004, AAMAS.

[8]  Steven L. Lytinen,et al.  Agent-based Simulation Platforms: Review and Development Recommendations , 2006, Simul..

[9]  Qiuming Zhu,et al.  Hierarchical Collective Agent Network (HCAN) for efficient fusion and management of multiple networked sensors , 2007, Inf. Fusion.

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

[11]  Abhishek Gupta,et al.  Decentralized Control of Multi-Agent Systems with an Adversarial Switching Topology , 2011 .

[12]  László Monostori,et al.  A Market Approach to Holonic Manufacturing , 1996 .

[13]  Fu-Shiung Hsieh.  Deadlock free task distribution and resource allocation for holonic manufacturing systems based on multi-agent framework , 2001, 2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236).

[14]  Fei Liu,et al.  Consensus problem of second-order multi-agent systems with time-varying communication delay and switching topology , 2011 .

[15]  Cesar Augusto Tacla,et al.  Holonic Control Metamodel , 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[16]  Michal Pechoucek,et al.  Holons & Agents: Recent Developments and Mutual Impacts , 2001, Multi-Agent-Systems and Applications.

[17]  Shihua Chen,et al.  Formation control for second-order multi-agent systems with time-varying delays under directed topology , 2012 .

[18]  Nick Collier,et al.  Repast: An extensible framework for agent simulation , 2001 .

[19]  Sanja Petrovic,et al.  SURVEY OF DYNAMIC SCHEDULING IN MANUFACTURING SYSTEMS , 2006 .

[20]  Nicholas R. Jennings,et al.  Market-Based Task Allocation Mechanisms for Limited-Capacity Suppliers , 2007, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[21]  Carlos Ramos,et al.  A holonic approach for task scheduling in manufacturing systems , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[22]  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.

[23]  K M Eriksson.  Book Review: Planning and Scheduling in Manufacturing and Services. Michael L. Pinedo, Springer-Verlag, £46.00 (ISBN 0 387 22198 0): , 2005 .

[24]  Ingo J. Timm,et al.  From Testing to Theorem Proving , 2006, Multiagent Engineering.

[25]  Reid G. Smith,et al.  The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver , 1980, IEEE Transactions on Computers.

[26]  Adriana Giret,et al.  A holonic architecture for the global road transportation system , 2010, J. Intell. Manuf..

[27]  Zhiqi Shen,et al.  An Efficient Task Allocation Protocol for P2P Multi-agent Systems , 2009, 2009 IEEE International Symposium on Parallel and Distributed Processing with Applications.

[28]  Pramod Kumar Jain,et al.  AGENT-BASED SIMULATION OF A SHOP FLOOR CONTROLLER USING HYBRID COMMUNICATION PROTOCOLS , 2007 .

[29]  Michael Pinedo,et al.  Planning and Scheduling in Manufacturing and Services , 2008 .

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

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

[32]  Qiuming Zhu.  Topologies of agents interactions in knowledge intensive multi-agent systems for networked information services , 2006, Adv. Eng. Informatics.

[33]  Clement H. C. Leung,et al.  Classification of Intelligent Agent Network Topologies and a New Topological Description Language for Agent Networks , 2006, Intelligent Information Processing.

[34]  Lihui Wu,et al.  Agent based production planning and scheduling system for networked manufacturing system , 2010, 2010 8th International Conference on Supply Chain Management and Information.

[35]  Manoj Kumar Tiwari,et al.  Infrastructure for co-ordination of multi-agents in a network–based manufacturing system , 2007 .

[36]  Robert L. Axtell,et al.  Effects of Interaction Topology and Activation Regime in Several Multi-Agent Systems , 2000, MABS.

[37]  Andrew Wallace.  Sequential resource allocation utilizing agents , 2003 .

[38]  Ming Kim Lim,et al.  Dynamically Integrated Manufacturing Systems (DIMS)—A Multiagent Approach , 2007, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[39]  Jacques Ferber,et al.  Multi-agent systems - an introduction to distributed artificial intelligence , 1999 .

[40]  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).

[41]  Toshihisa Funabashi,et al.  Multi‐agent‐based autonomous power distribution network restoration using contract net protocol , 2009 .

[42]  Paulo Leitão,et al.  A Holonic Approach to Dynamic Manufacturing Scheduling , 2006, BASYS.

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

[44]  Yichuan Jiang,et al.  A multi-agent coordination model for the variation of underlying network topology , 2005, Expert Syst. Appl..

[45]  Jing Hu,et al.  Decision Making of Networked Multiagent Systems for Interaction Structures , 2011, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[46]  Paul Valckenaers,et al.  Aspects of co-operation in distributed manufacturing systems , 1999 .

[47]  Kung-Jeng Wang,et al.  Bid construction scheme for job flow time reduction in auction-based fully-distributed manufacturing systems , 2006 .

[48]  László Monostori,et al.  Agent-based systems for manufacturing , 2006 .

[49]  Saeed Mansour,et al.  Dynamic flexible job shop scheduling with alternative process plans: an agent-based approach , 2011 .

[50]  Albert Jones,et al.  Survey of Job Shop Scheduling Techniques , 1999 .

[51]  Q. Zhu,et al.  The topologies of cooperation in knowledge intensive multi-agent systems , 2003, IEMC '03 Proceedings. Managing Technologically Driven Organizations: The Human Side of Innovation and Change (IEEE Cat. No.03CH37502).

[52]  Clement H. C. Leung,et al.  Topological analysis of AOCD-based agent networks and experimental results , 2008, J. Comput. Syst. Sci..

[53]  Krishna R. Pattipati,et al.  Integration of a Holonic Organizational Control Architecture and Multiobjective Evolutionary Algorithm for Flexible Distributed Scheduling , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.