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This model provides high descriptive possibilities but the associated preferences generally do not meet the Bellman principle, thus preventing any straightforward adaptation of MODP. To overcome this difficulty, we introduce here a general family of dominance rules enabling an early pruning of some Pareto-optimal sub-solutions that cannot lead to a Choquet optimum. Within this family, we identify the most efficient dominance rules and show how they can be incorporated into a MODP algorithm. Then we report numerical tests showing the actual efficiency of this approach to find Choquet-optimal tradeoffs in multiobjective knapsack problems.","doi":null,"url":"https://ijcai.org/proceedings/2013/87","pdf":"https://ijcai.org/proceedings/2013/0087.pdf","markdown":"https://ijcai.org/proceedings/2013/87.md","bibtex":"https://ijcai.org/proceedings/2013/bibtex/87","volume":{"slug":"2013","title":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2013","url":"https://ijcai.org/proceedings/2013/","year":2013,"location":"Beijing, China","dates":"3–9 August 2013","editors":"Francesca Rossi","isbn":"978-1-57735-633-2","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":87,"pages":{"first":538,"last":543},"keywords":[],"videos":[],"references":[{"position":1,"raw":"[Bellman, 1957] R. Bellman. Dynamic Programming. 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