Advertisement

Genetic Local Search in an Automated Contracting Environment

  • Ma. Fe R. Alvarez
  • Remedios de Dios Bulos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2738)

Abstract

In automated contracting, bid evaluation is a complex process because the task of finding the optimal set of bids requires the consideration of several factors such as time constraints, risk estimates and price. There have been attempts in the recent past (such as the use of simulated-annealing) to solve the bid evaluation problem in an automated contracting environment. This research endeavors to offer a better alternative to the solution of the bid evaluation problem by adopting the genetic local search (GLS) method.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aarts, E., Stehouwer, H.P.: Neural Networks and the Travelling Salesman Problem. In: Proceedings International Conference on Artificial Neural Networks, pp. 960–966. Springer, Heidelberg (1993)Google Scholar
  2. 2.
    Alvarez, M. F. R.: A Genetic Local Search Approach To The Bid Evaluation Problem In An Automated Contracting Environment. A Thesis Presented to the Faculty of the Graduate School of the College of Computer Studies, De La Salle University (2002) Google Scholar
  3. 3.
    Bakos, Y.: The Emerging Role of Electronic Marketplaces on the Internet. Communications of the ACM, 33–42 (1998)Google Scholar
  4. 4.
    Beam, C., Segev, A.: Automated Negotiations: A Survey of the State of the Art. Technical Report CITM Working Paper 96-WP-1022, Walter A. Hass School of Business (1997)Google Scholar
  5. 5.
    Collins, J., Sundareswara, R., Tsvetovat, M., Gini, M., Mobasher, B.: Search Strategies for Bid Selection in Multi-Agent Contracting. Agent-mediated Electronic Commerce. In: Proceedings of IJCAI 1999, Stockholm, Sweden (1999)Google Scholar
  6. 6.
    Collins, J., Sundareswara, R., Tsvetovat, M., Gini, M., Mobasher, B.: Multi- Agent Contracting for Supply-Chain Management. Technical Report 00-010, University of Minnesota (2000)Google Scholar
  7. 7.
    Durbin, R., Sacliski, R., Yuille, A.: An Analysis of the Elastic Net Approach to the Traveling Salesman Problem. Neural Computation 1, 348–358 (1989)CrossRefGoogle Scholar
  8. 8.
    Fiechter, L.: A Parallel Tabu Seach Algorithm for Large Traveling Salesman Problems. Discrete Applied Mathematics and Combinatorial Operations Research and Computer Science, 243–267 (1994)Google Scholar
  9. 9.
    Freisleben, B., Schulte, M.: Combinatorial Optimization with Parallel Adaptive Threshold Accepting. In: Proceedings of 1992 European Workshop on Parallel Computing, Barcelona, pp. 176–179. TOS Press (1992)Google Scholar
  10. 10.
    Freisleben, B., Merz, P.: A Genetic Local Search Algorithm for Solving Symmetric and Asymmetric Traveling Salesman Problems. In: Proceedings of the 1996 IEEE International Conference on Evolutionary Computation, Nagoya, Japan, pp. 616–621 (1996)Google Scholar
  11. 11.
    Gambardella, L.M., Dorigo, M.: Ant-Q: A Reinforcement Learning Approach to the Travelling Salesman Problem. In: Proceedings of 18th International Conference on Machine Learning, pp. 252–260. Morgan Kaufmann, San Francisco (1996)Google Scholar
  12. 12.
    Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)zbMATHGoogle Scholar
  13. 13.
    Guttman, R., Maes, P.: Cooperative vs. Competitive Multi-agent Negotiations in Retail Electronic Commerce. In: 2nd International Workshop on Cooperative Information Agents (1998) Google Scholar
  14. 14.
    Guttman, R., Moukas, A., Maes, P.: Agent-mediated Electronic Commerce: A Survey. Knowledge Engineering Review (1998) Google Scholar
  15. 15.
    Homaifar, L., Guan, C., Liepins, G.: A New Approach to the Travelling Salesman Problem by Genetic Algorithms. In: Proc. 5th International Conference on Genetic Algorithms, pp. 460–466. Morgan Kaufmann, San Francisco (1993)Google Scholar
  16. 16.
    Merz, P., Freisleben, B.: Genetic Local Search for the TSP: New Results. In: Proceedings of the 1997 IEEE International Conference on Evolutionary Computation, pp. 159–164. IEEE Press, Los Alamitos (1997)CrossRefGoogle Scholar
  17. 17.
    Merz, P., Freisleben, B.: On the Effectiveness of Evolutionary Search in High-Dimensional NK-Landscapes. In: Proceedings of the 1998 IEEE International Conference on Evolutionary Computation, pp. 741–745. IEEE Press, Los Alamitos (1998)Google Scholar
  18. 18.
    Merz, P., Freisleben, B.: A Genetic Local Search Approach to the Quadratic Assignment Problem (1999) (a manuscript) Google Scholar
  19. 19.
    Merz, P., Freisleben, B.: Fitness Landscapes, Memetic Algorithms and Greedy Operators for Graph Bi-Partitioning. Evolutionary Computation (1999) Google Scholar
  20. 20.
    Merz, P., Freisleben, B.: Genetic Algorithms for Binary Quadratic Programming. In: Proceedings of the Genetic and Evolutionary Computation Conference. Morgan Kaufmann, San Francisco (1999)Google Scholar
  21. 21.
    Reinelt, G.: The Traveling Salesman. LNCS, vol. 840. Springer, Heidelberg (1994)zbMATHGoogle Scholar
  22. 22.
    Sycara, K., Decker, K., Williamson, M.: Middle-agents for the Internet. In: Proceedings of the 15th Joint Conference on Artificial Intelligence (1997)Google Scholar
  23. 23.
    Ulder, N., Aarts, E., Bandelt, H., van Laarhoven, P., Pesch, E.: Genetic Local Search Algorithms for the Traveling Salesman Problem. In: Schwefel, H.-P., Männer, R. (eds.) PPSN 1990. LNCS, vol. 496, pp. 109–116. Springer, Heidelberg (1991)CrossRefGoogle Scholar
  24. 24.
    Van Laarhoven, P., Aarts, E.H.L.: Simulated Annealing: Theory and Applications. Kluwer Academic Publishers, Dordrecht (1987)zbMATHGoogle Scholar
  25. 25.
    Wagner, G.: A UML Profile for External AOR Models. In: Giunchiglia, F., Odell, J.J., Weiss, G. (eds.) AOSE 2002. LNCS, vol. 2585, pp. 99–110. Springer, Heidelberg (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Ma. Fe R. Alvarez
    • 1
  • Remedios de Dios Bulos
    • 1
  1. 1.College of Computer StudiesDe La Salle UniversityManilaPhilippines

Personalised recommendations