The simple supply chain model and evolutionary computation

2003 Congress on Evolutionary Computation, CEC 2003 - Proceedings

Volumn 4, Issue , 2003, Pages 2322-2329

  Gosling, T ^a  

^a UNIVERSITY OF ESSEX   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

MANAGEMENT INFORMATION SYSTEMS;

POPULATION BASED INCREMENTAL LEARNING; SUPPLY CHAIN MODELING;

CALCULATIONS;

EID: 84901440413     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2003.1299378     Document Type: Conference Paper

References (11)

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2. Sandholm, T.: Distributed Rational Decision Making. In: Weiss, C. (ed.): Multiagent Systems A Modern Approach to Distributed Artificial Intelligence. MIT press 1999, pp. 201
3. W. E. Walsh, Market Protocols for Decentralized Supply Chain Formation, Doctoral Thesis submitted to the University Of Michigan (2001)
4. P. Anthony and N. R. Jennings, A heuristic bidding strategy for multiple heterogeneous auctions, Proc. 5th Int. Conf. on Electronic Commerce, Pittsburgh, USA (2003)
5. P. Faratin, C. Sierra and N. R. Jennings, Using similarity criteria to make negotiation trade-offs. Proc. 4th Int. Conf. on Multi-Agent Systems (ICMAS-2000), Boston. USA, 119-126 (2000).
6. M, P. Wellman. A. Greenwald. P. Stone and P. R. Wurman, The 2001 Trading Agent Competition, Fourteenth Conference on Innovative Applications of Artificial Intelligence (2000)
7. N. Matos, C. Sierra and N. Jennings, Determining Successful Negotiation Strategies: An Evolutionary Approach, Proceedings of the 3rd International Conference on Multi-Agent Systems (ICMAS-98)
8. Shumeet Baluja, Population Based Incremental Learning - A Method for Integrating Genetic Search Based Function Optimisation and Competitive Learning, (Tech. Rep. No. CMU-CS-94-163). Pittsburgh, PA: Carnegie Mellon University (1994)
9. R. Sukthankar, S. Baluja. J. Hancock, Multiple Adaptive Agents for Tactical Driving, Applied Intelligence (1998)
10. M. Sebag, A. Ducoulombier, Extending population-based incremental learning to continuous search spaces, In Th. Back, G. Eiben, M, Schoenauer, and H.-P. Schwefel, editors, Proceedings of the 5 th Conference on Parallel Problems Solving from Nature, pages 418-427. Springer Verlag, (1998)
11. I. Inza, M. Merino, P. Larra-naga, J. Quiroga. B. Sierra, M. Girala, Feature Subset Selection by Population-Based Incremental Learning. A case study in the survival of cirrhotic patients treated with TIPS, Tehnicat Report no. EHU-KZAA-IK-1/99. University of the Basque Country, Spain. (1999)