Paper:
A Qualitative Reasoning Model for Tradeoff Analysis in Multiple Objective Decision Making
Tom Wanyama and Behrouz Homayoun Far
Department of Electrical and Computer Engineering, University of Calgary, 2500 University Drive, N.W. Calgary, Alberta, Canada, T2N 1N4
In Multi-Criteria Decision Making problems such as choosing a development policy, selecting software products, or searching for commodities to purchase, it is often necessary to evaluate solution options in respect of multiple objectives. The solution alternative that performs best in all the objectives is the dominant solution, and it should be selected to solve the problem. However, usually the selection objectives are incomparable and conflicting, making it impossible to have a dominant solution among the alternatives. In such cases, tradeoff analysis is required to identify the objectives that can be optimized, and those that can be comprised in order to choose a winning solution. In this paper we present a tradeoff analysis model based on the principles of qualitative reasoning that provides visualization support for understanding interaction and tradeoff dependences among solutions evaluation criteria which affect the tradeoff among selection objectives. Moreover, the decision support system based on our tradeoff analysis model facilitates discovery of hidden solution features so as improve the completeness and certainty of the user preference model.
- [1] A. Mohamed, T. Wanyama, G. Ruhe, A. Eberlein, and B. Far, “COTS Evaluation Supported By Knowledge Bases,” LNCS 3096, pp. 43-54, 2004.
- [2] B. Kuipers, “Commonsense Reasoning about Causality: Deriving Behavior from Structure,” Artificial Intelligence, Vol.24, Issue 1-3, pp. 169-203, December, 1984.
- [3] B. Kuipers, C. Chiu, D. T. D. Molle, and D. Throop, “Higher-Order Derivative Constraints in Qualitative Simulation,” Artificial Intelligence, Vol.51, pp. 343-379, 1991.
- [4] B. W. Boehm, C. M. Abts, and E. K. Bailey, “COCOTS Software Integration Cost Model: an Overview,” Proceedings of the California Software Symposium, October, 1998.
- [5] C. J. Petrie, T. A. Webster, and M. R. Cutkosky, “Using Pareto Optimality to Coordinate Distributed Agents,” AIEDAM Special Issue on Conflict Management, Vol.9, pp. 269-281, 1995.
- [6] CeBASE COTS lessons learned Repository, available at
http://www.cebase.org - [7] International Organization for Standardization: Software Products Evaluation – Quality Characteristics and Guidelines, Geneva, Switzerland: International Organization for Standardization (ISO), 1991.
- [8] J. J. Dujmovic and W. Y. Fang, “Reliability of LSP Criteria,” LNAI 3131, pp. 151-162, 2004.
- [9] P. Pu and D. Lalanne, “Design Visual Thinking Tools for Mixed Initiative Systems,” International Conference on Intelligent User Interfaces, 2002.
- [10] P. Pu, P. Kumar, and B. Faltings, “User-Involved Tradeoff Analysis in Configuration Tasks,” Workshop notes, Third International Workshop on User-Interaction in Constraint Satisfaction, at the Ninth International Conference on Principles and Practice of Constraint Programming, 2003.
- [11] T. Wanyama and B. H. Far, “Multi-Agent System for Group-Choice Negotiation and Decision Support,” Proceedings of the 3rd Workshop on Agent Oriented Information Systems at the Autonomous Agents and Multi-Agent Systems Conference, New York, USA, July, 2004.
- [12] V. Torra, “The Weighted OWA operator,” International Journal of Intelligent Systems, Vol.12, pp. 153-166, 1997.
- [13] W. F. Bialas, “Cooperative n-Person Stackelberg Games,” Proceeding of the 28th IEEE Conference on Decision and Control, May, 1998.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.