Supply Chain Coordination Using an Adaptive Distributed Search Strategy

A tree search strategy is said to be adaptive when it dynamically identifies which areas of the tree are likely to contain good solutions, using information that is gathered during the search process. This study shows how an adaptive approach can be used to enhance the efficiency of the coordination process of an industrial supply chain. The result is a new adaptive method (called the adaptive discrepancy search), intended for search in nonbinary trees, and that is exploitable in a distributed optimization context. For the industrial case studied (a supply chain in the forest products industry), this allowed reducing nearly half the time needed to obtain the best solution in comparison with a standard nonadaptive method. The method has also been evaluated for use with synthesized problems in order to validate the results that are obtained and to illustrate different properties of the algorithm.

[1]  Sophie D'Amours,et al.  Agent-Based Supply Chain Planning in the Forest Products Industry , 2006, BASYS.

[2]  John Collins,et al.  The Supply Chain Management Game for the 2007 Trading Agent Competition , 2004 .

[3]  Mark S. Fox,et al.  Agent-Oriented Supply-Chain Management , 2000 .

[4]  Gérard P. Cachon.  Supply Chain Coordination with Contracts , 2003, Supply Chain Management.

[5]  Andreas Fink,et al.  Supply Chain Coordination by Means of Automated Negotiations Between Autonomous Agents , 2006 .

[6]  W. Ruml,et al.  Heuristic Search in Bounded-depth Trees: Best-Leaf-First Search , 2002 .

[7]  Gilles Pesant,et al.  Discrepancy-Based Method for Hierarchical Distributed Optimization , 2007 .

[8]  Wady Naanaa,et al.  YIELDS: A Yet Improved Limited Discrepancy Search for CSPs , 2007, CPAIOR.

[9]  Leonid Sheremetov,et al.  Supply chain network optimization based on collective intelligence and agent technologies , 2008 .

[10]  William H. Press,et al.  Numerical recipes in C. The art of scientific computing , 1987 .

[11]  Thierry Moyaux,et al.  Supply Chain Management and Multiagent Systems: An Overview , 2006 .

[12]  R. Wallace,et al.  Learning from Failure in Constraint Satisfaction Search , 2006 .

[13]  Christoph Schneeweiss,et al.  Hierarchical coordination mechanisms within the supply chain , 2004, Eur. J. Oper. Res..

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

[15]  Lakhdar Sais,et al.  Boosting Systematic Search by Weighting Constraints , 2004, ECAI.

[16]  Patrice Boizumault,et al.  Σ-All Different: Softening AllDifferent in Weighted CSPs , 2007 .

[17]  Jonathan Gaudreault,et al.  Agent-based supply-chain planning in the forest products industry , 2007 .

[18]  Mauro Brunato,et al.  Reactive Search and Intelligent Optimization , 2008 .

[19]  Charu Chandra,et al.  Information Technology Support for Integrated Supply Chain Modeling , 2008 .

[20]  Hartmut Stadtler,et al.  Supply chain management and advanced planning--basics, overview and challenges , 2005, Eur. J. Oper. Res..

[21]  Mark S. Boddy,et al.  An Analysis of Time-Dependent Planning , 1988, AAAI.

[22]  Susan L. Epstein,et al.  LEARNING TO SUPPORT CONSTRAINT PROGRAMMERS , 2005, Comput. Intell..

[23]  Sophie D'Amours,et al.  Combined planning and scheduling in a divergent production system with co-production: A case study in the lumber industry , 2011, Comput. Oper. Res..

[24]  Arnoldo C. Hax,et al.  Production and inventory management , 1983 .

[25]  Alan J. Hu,et al.  Boosting Verification by Automatic Tuning of Decision Procedures , 2007 .

[26]  Jayashankar M. Swaminathan,et al.  Modeling Supply Chain Dynamics: A Multiagent Approach , 1998 .

[27]  J. Shapiro.  Modeling the Supply Chain , 2000 .

[28]  Gilles Pesant,et al.  Distributed search for supply chain coordination , 2009, Comput. Ind..

[29]  W. Press,et al.  Numerical Recipes: The Art of Scientific Computing , 1987 .

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

[31]  Philippe Refalo,et al.  Impact-Based Search Strategies for Constraint Programming , 2004, CP.

[32]  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).

[33]  Matthew L. Ginsberg,et al.  Limited Discrepancy Search , 1995, IJCAI.

[34]  Jean-Marc Frayret,et al.  A multidisciplinary review of collaborative supply chain planning , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[35]  Sameer Kumar,et al.  Utilizing analytic hierarchy process for improved decision making within supply chains , 2008 .

[36]  Christoph A. Schneeweiss,et al.  Distributed Decision Making , 2003 .

[37]  V. Lesser.  An Overview of Dai: Viewing Distributed Ai as Distributed Search 1 , 1990 .

[38]  Philippe Baptiste,et al.  Heuristic Control of a Constraint-Based Algorithm for the Preemptive Job-Shop Scheduling Problem , 1999, J. Heuristics.

[39]  Mark K. Goldberg,et al.  Discovering Optimization Algorithms Through Automated Learning , 2001, Graphs and Discovery.

[40]  D. Marquardt.  An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[41]  Makoto Yokoo,et al.  Distributed Partial Constraint Satisfaction Problem , 1997, CP.

[42]  Hartmut Stadtler,et al.  Negotiation-based collaborative planning between supply chains partners , 2005, Eur. J. Oper. Res..

[43]  Patrick Beaumont.  Multi-platform coordination and resource management in command and control , 2004 .

[44]  S. Goyal,et al.  Models for multi-plant coordination , 1993 .

[45]  S. Shieber,et al.  Adaptive tree search , 2002 .

[46]  Patrice Boizumault,et al.  A Value Ordering Heuristic for Weighted CSP , 2007 .

[47]  Norman M. Sadeh,et al.  Pushing the Limits of Rational Agents: The Trading Agent Competition for Supply Chain Management , 2010, AI Mag..

[48]  Brahim Chaib-draa,et al.  Information Sharing as a Coordination Mechanism for Reducing the Bullwhip Effect in a Supply Chain , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[49]  Jonathan Gaudreault,et al.  DISTRIBUTED OPERATIONS PLANNING IN THE LUMBER SUPPLY CHAIN: MODELS AND COORDINATION. , 2010 .

[50]  J. Rice,et al.  SUPPLY CHAIN VS. SUPPLY CHAIN: THE HYPE AND THE REALITY. , 2001 .

[51]  Sylvain Lamprier,et al.  Document Length Normalization by Statistical Regression , 2007 .