SoCS 2019
A General Interactive Approach for Solving Multi-Objective Combinatorial Optimization Problems with Imprecise Preferences
Abstract
In this paper, we develop a general interactive method to solve multi-objective combinatorial optimization problems with imprecise preferences. Assuming that preferences can be represented by a parameterized scalarizing function, we iteratively ask preferences queries to the decision maker in order to reduce the uncertainty over the preference parameters until being able to determine her preferred solution. To produce informative preference queries at each step, we generate promising solutions using the extreme points of the polyhedron representing the admissible preference parameters and then we ask the decision maker to compare two of these solutions (we propose different selection strategies). These extreme points are also used to provide a stopping criterion guaranteeing that the returned solution is optimal (or near-optimal) according to the decision maker
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Context
- Venue
- International Symposium on Combinatorial Search
- Archive span
- 2010-2024
- Indexed papers
- 598
- Paper id
- 432614696723916362