Distributed coordination of project schedule changes using agent-based compensatory negotiation methodology

In the construction industry, projects are becoming increasingly large and complex, necessitating multiple subcontractors. Traditional centralized coordination techniques used by general contractors become insufficient as subcontractors perform most work and provide their own resources. When subcontractors cannot provide enough resources, they hinder their own performance, that of other subcontractors, and ultimately the entire project. Thus, projects need a new distributed coordination approach wherein all of the concerned subcontractors can respond to changes and reschedule a project dynamically. This paper presents a new distributed coordination framework for project schedule changes (DCPSC) that is based on an agent-based negotiation approach wherein software agents evaluate the impact of changes, simulate decisions, and give advice on behalf of the human subcontractors. A case example demonstrates the significance of the DCPSC. It compares two centralized coordination methodologies used in current practice to the DCPSC framework. We demonstrate that our DCPSC framework always finds a solution that is better than or equal to any of two centralized coordination methodologies.

[1]  Norman M. Sadeh,et al.  Distributed constrained heuristic search , 1991, IEEE Trans. Syst. Man Cybern..

[2]  Martin Fischer,et al.  Importance of Capacity Constraints to Construction Cost and Schedule , 2000 .

[3]  Carl A. Waldspurger,et al.  Enterprise: a Market-like Task Scheduler for Distributed Computing Environments. [2] A. Barak and A. Shiloh. a Distributed Load-balancing Policy for a Multicomputer. Software Practice Load Balancing for Massively-parallel Soft-real-time Systems. Knowledge Systems Lab- Iteration Step Figure 13: Fairn , 1991 .

[4]  Makoto Yokoo,et al.  Distributed constraint satisfaction for formalizing distributed problem solving , 1992, [1992] Proceedings of the 12th International Conference on Distributed Computing Systems.

[5]  Iris D. Tommelein,et al.  Interactive Coordination of Distributed Work Plans , 2000 .

[6]  Michael P. Wellman A Market-Oriented Programming Environment and its Application to Distributed Multicommodity Flow Problems , 1993, J. Artif. Intell. Res..

[7]  Makoto Yokoo,et al.  Constraint Satisfaction Problem , 2001 .

[8]  Austin Tate,et al.  A distributed scheduling framework , 1994, Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94.

[9]  Yoav Shoham,et al.  A Dynamic Theory of Incentives in Multi-Agent Systems , 1997, IJCAI.

[10]  Makoto Yokoo,et al.  The Distributed Constraint Satisfaction Problem: Formalization and Algorithms , 1998, IEEE Trans. Knowl. Data Eng..

[11]  Jeffrey S. Rosenschein,et al.  Designing Conventions for Automated Negotiation , 1994, AI Mag..

[12]  Charles J. Petrie,et al.  Agent-Based Engineering, the Web, and Intelligence , 1996, IEEE Expert.

[13]  Khaled A El-Rayes,et al.  Resource-driven scheduling of repetitive activities , 1998 .

[14]  Jeffrey S. Rosenschein,et al.  Rules of Encounter - Designing Conventions for Automated Negotiation among Computers , 1994 .

[15]  James M. Antill,et al.  Critical path methods in construction practice , 1970 .

[16]  Albert Thumann,et al.  Project management for engineering and construction , 1989 .

[17]  J. W. Gale Critical Path Methods , 1967 .

[18]  S. Keoki. Sears,et al.  Construction Project Management , 1972 .

[19]  Michael R. Genesereth,et al.  Agent-based framework for integrated facility engineering , 1993, Engineering with Computers.

[20]  William J. O'Brien,et al.  An economic view of project coordination , 1995 .

[21]  Charles Char-Lin Koo A distributed model for performance systems: synchronizing plans among intelligent agents via communication , 1988 .

[22]  A. Feldman Welfare economics and social choice theory , 1980 .

[23]  Tuomas Sandholm,et al.  An Implementation of the Contract Net Protocol Based on Marginal Cost Calculations , 1993, AAAI.

[24]  Timothy W. Finin,et al.  KQML as an agent communication language , 1994, CIKM '94.

[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]  Edmund H. Durfee,et al.  Coordination as distributed search in a hierarchical behavior space , 1991, IEEE Trans. Syst. Man Cybern..

[27]  Edmund H. Durfee,et al.  A contracting model for flexible distributed scheduling , 1996, Ann. Oper. Res..

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

[29]  John W. Fondahl The Development of the Construction Engineer: Past Progress and Future Problems , 1991 .

[30]  Victor R. Lesser,et al.  Generalizing the Partial Global Planning Algorithm , 1992, Int. J. Cooperative Inf. Syst..

[31]  Katia Sycara,et al.  Multiagent Compromise via Negotiation , 1989, Distributed Artificial Intelligence.

[32]  Iris D. Tommelein,et al.  WORKPLAN: CONSTRAINT-BASED DATABASE FOR WORK PACKAGE SCHEDULING , 1999 .

[33]  Eithan Ephrati,et al.  Deriving Consensus in Multiagent Systems , 1996, Artif. Intell..

[34]  Yan Jin,et al.  i-AGENTS: Modeling Organizational Problem Solving in Multi-Agent Teams , 1993 .

[35]  Charles J. Petrie,et al.  Agent-Based Project Management , 1999, Artificial Intelligence Today.

[36]  J W Fondahl,et al.  A non-computer approach to the critical path method , 1962 .