A Support-Based Propagator for the Bi-Objective Pareto Constraint

Hartert, Renaud;Schaus, Pierre
(2014) The Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14) — Location: Québec (27.July.2014)

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(en) Bi-Objective Combinatorial Optimization problems are ubiquitous in real-world applications and designing approaches to solve them efficiently is an important research area of Artificial Intelligence. In Constraint Programming, the recently introduced bi-objective Pareto constraint allows one to solve bi-objective combinatorial optimization problems exactly. Using this constraint, every non-dominated solution is collected in a single tree-search while pruning sub-trees that cannot lead to a non-dominated solution. This paper introduces a simpler and more efficient filtering algorithm for the bi-objective Pareto constraint. The efficiency of this algorithm is experimentally confirmed on classical bi-objective benchmarks.
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Hartert, R., & Schaus, P. (2014). A Support-Based Propagator for the Bi-Objective Pareto Constraint. The Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14), Québec. https://hdl.handle.net/2078.5/230408