Multi-agent technology for scheduling and control projects in multi-project environments. An Auction based approach

Most existing methods for scheduling projects are based on centralized or hierarchical decision making using global models. So far, these methods have not produced the desired results, especially in highly dynamic multi-projects environments. In this study, we investigate a new method based on multi-agent systems and a combinatorial auction mechanism to allocate resources for the projects tasks. In combinatorial auction the bidders demand a combination of dependent goods with a single bid. We consider basically two types of agents, projects and resources. Projects are the bidders and resources are the goods. An auction mechanism based on Lagrangian- based decomposition is designed to achieve efficient allocation resources. Our approach allows manage some traditional aspects of multi-project environments: dynamic addition of resources or projects, changes of the resources capabilities, allocation flexibility, etc.

[1]  Lawrence Cabac.  Multi-Agent System: A Guiding Metaphor for the Organization of Software Development Projects , 2007, MATES.

[2]  José Manuel Galán,et al.  Diffusion of Domestic Water Conservation Technologies in an ABM-GIS Integrated Model , 2008, HAIS.

[3]  Jürgen Bode,et al.  Application of multiagent systems in project management , 2000 .

[4]  Hsing-Pei Kao,et al.  An event-driven approach with makespan/cost tradeoff analysis for project portfolio scheduling , 2006, Comput. Ind..

[5]  Boyd C. Paulson,et al.  Agent-Based Compensatory Negotiation Methodology to Facilitate Distributed Coordination of Project Schedule Changes , 2003 .

[6]  Jorge J. Gómez-Sanz,et al.  Agent Oriented Software Engineering with INGENIAS , 2003, CEEMAS.

[7]  Soundar Kumara,et al.  Distributed Multiproject Resource Control: A Market-Based Approach , 2002 .

[8]  Giuseppe Confessore,et al.  A market-based multi-agent system model for decentralized multi-project scheduling , 2007, Ann. Oper. Res..

[9]  Avraham Shtub,et al.  Multi-Project Scheduling and Control: A Process-Based Comparative Study of the Critical Chain Methodology and Some Alternatives , 2004 .

[10]  Boaz Golany,et al.  Managing multi-project environments through constant work-in-process , 2003 .

[11]  Hans Akkermans,et al.  Decentralized Markets versus Central Control: A Comparative Study , 1999, J. Artif. Intell. Res..

[12]  Charles J. Petrie,et al.  Agent-Based Project Schedule Coordination , 2000 .

[13]  X. Zhao,et al.  Surrogate Gradient Algorithm for Lagrangian Relaxation , 1999 .

[14]  S. Clearwater.  Market-based control: a paradigm for distributed resource allocation , 1996 .

[15]  Willy Herroelen,et al.  A hierarchical approach to multi-project planning under uncertainty , 2004 .

[16]  Dilip B. Kotak,et al.  Agent-based collaborative project management system for distributed manufacturing , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[17]  Peter B. Luh,et al.  Scheduling of manufacturing systems using the Lagrangian relaxation technique , 1991, IEEE Trans. Autom. Control..

[18]  Boyd C. Paulson,et al.  Multi‐Agent Distributed Coordination of Project Schedule Changes , 2003 .

[19]  Peter B. Luh,et al.  An optimization-based algorithm for job shop scheduling , 1997 .

[20]  Charles J. Petrie,et al.  Distributed coordination of project schedule changes using agent-based compensatory negotiation methodology , 2003, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[21]  Nicholas R. Jennings,et al.  Applying agent technology , 1995, Appl. Artif. Intell..

[22]  Barbara Messing,et al.  An Introduction to MultiAgent Systems , 2002, Künstliche Intell..

[23]  Soundar R. T. Kumara,et al.  Multiagent based dynamic resource scheduling for distributed multiple projects using a market mechanism , 2003, J. Intell. Manuf..