Abstract
We propose a general methodology for approximating the Pareto front of multi-criteria optimization problems. Our search-based methodology consists of submitting queries to a constraint solver. Hence, in addition to a set of solutions, we can guarantee bounds on the distance to the actual Pareto front and use this distance to guide the search. Our implementation, which computes and updates the distance efficiently, has been tested on numerous examples. © 2010 Springer-Verlag.
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CITATION STYLE
Legriel, J., Le Guernic, C., Cotton, S., & Maler, O. (2010). Approximating the Pareto front of multi-criteria optimization problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6015 LNCS, pp. 69–83). https://doi.org/10.1007/978-3-642-12002-2_6
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