Approximate Pareto sets of minimal size for multi-objective optimization problems

Cristina Bazgan (1) , Florian Jamain (1) , Daniel Vanderpooten (1)

1 LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision

We are interested in a problem introduced by Vassilvitskii and Yannakakis (2005), the computation of a minimum set of solutions that approximates within an accuracy εε the Pareto set of a multi-objective optimization problem. We mainly establish a new 3-approximation algorithm for the bi-objective case. We also propose a study of the greedy algorithm performance for the tri-objective case when the points are given explicitly, answering an open question raised by Koltun and Papadimitriou in (2007).

Mots clés: Pareto set; Multi-objective optimization; Greedy algorithm; Approximation algorithm; Non-dominated points

Domaines: Informatique [cs]

Cristina Bazgan, Florian Jamain, Daniel Vanderpooten. Approximate Pareto sets of minimal size for multi-objective optimization problems. Operations Research Letters, 2015, 43 (1), ⟨10.1016/j.orl.2014.10.003⟩. ⟨hal-01505524⟩