15th European Conference on Artificial Intelligence
|July 21-26 2002 Lyon France|
Constraint Satisfaction and Optimization are important areas of Artificial Intelligence. However, in many real-life applications, more functions should be optimized at the same time; the user needs to be provided a set of solutions and a posteriori choose the most preferable. In this paper, we propose an algorithm for solving Multi-Criteria Optimization problems in this setting. The algorithm is complete, i.e., it finds all the non-dominated solutions, and does not make any assumption on the structure of the constraints nor on the type of the objective functions. It exploits Point Quad-Trees for the representation of the non-dominated frontier, in order to efficiently access the data. We describe the implementation and give experimental results showing that our algorithm outperforms widely used methods.
Keywords: Constraint Programming, Constraint Satisfaction, Search
Citation: Marco Gavanelli: An Algorithm for Multi-Criteria Optimization in CSPs. In F. van Harmelen (ed.): ECAI2002, Proceedings of the 15th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2002, pp.136-140.