Surrogate upper bound sets for bi-objective bi-dimensional binary knapsack problems - Archive ouverte HAL Access content directly
Journal Articles European Journal of Operational Research Year : 2015

Surrogate upper bound sets for bi-objective bi-dimensional binary knapsack problems

Abstract

The paper deals with the definition and the computation of surrogate upper bound sets for the bi-objective bi-dimensional binary knapsack problem. It introduces the Optimal Convex Surrogate Upper Bound set, which is the tightest possible definition based on the convex relaxation of the surrogate relaxation. Two exact algorithms are proposed: an enumerative algorithm and its improved version. This second algorithm results from an accurate analysis of the surrogate multipliers and the dominance relations between bound sets. Based on the improved exact algorithm, an approximated version is derived. The proposed algorithms are benchmarked using a dataset composed of three groups of numerical instances. The performances are assessed thanks to a comparative analysis where exact algorithms are compared between them, the approximated algorithm is confronted to an algorithm introduced in a recent research work.
No file

Dates and versions

hal-01158355 , version 1 (31-05-2015)

Identifiers

Cite

Audrey Cerqueus, Anthony Przybylski, Xavier Gandibleux. Surrogate upper bound sets for bi-objective bi-dimensional binary knapsack problems. European Journal of Operational Research, 2015, 244 (2), pp.417-433. ⟨10.1016/j.ejor.2015.01.035⟩. ⟨hal-01158355⟩
192 View
0 Download

Altmetric

Share

Gmail Facebook X LinkedIn More