Abstract
Partial orders provide a convenient way to express preferences on multiple criteria. Prominent examples are Pareto-dominance and the preference relations of (T)CP-nets [1]. In advanced personalized recommender systems, the user may also specify a partial order over the possible values of a single criterion. We introduce a technique called outer branching to compute the non-dominated frontier of optimization problems with partial orders. It can be used to compute all Pareto-optimal solutions for n criteria by performing a systematic search over the criteria space. Dominance constraints avoid the generation of non-optimal solutions.
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Ulrich, J. (2009). Outer Branching: How to Optimize under Partial Orders?. In: Barichard, V., Ehrgott, M., Gandibleux, X., T'Kindt, V. (eds) Multiobjective Programming and Goal Programming. Lecture Notes in Economics and Mathematical Systems, vol 618. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85646-7_10
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DOI: https://doi.org/10.1007/978-3-540-85646-7_10
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