Improved linearized models for Graph Partitioning Problem under Capacity Constraints - Archive ouverte HAL Access content directly
Journal Articles Optimization Methods and Software Year : 2017

Improved linearized models for Graph Partitioning Problem under Capacity Constraints

Abstract

We investigate a variant of the Graph Partitioning Problem with capacity constraints imposed on the clusters, giving rise to quadratic constraints in 0–1 formulations. Several compact linearized models of the problem are proposed and analysed: (a) a model featuring binary variables which results from the application of the standard Fortet linearization technique; (b) a more compact model featuring only binary variables, obtained by linearization after reformulation of the quadratic constraints as bilinear constraints; (c) a strengthened version of the latter model, still featuring variables. Computational experiments comparing the relative strength and efficiency of the various models on a series of test instances involving complete graphs with up to 50 nodes are reported and discussed.
Fichier principal
Vignette du fichier
Nguyen_2017_Improved_linearized.pdf (351.29 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01369135 , version 1 (30-06-2017)

Identifiers

Cite

Viet Hung Nguyen, Michel Minoux. Improved linearized models for Graph Partitioning Problem under Capacity Constraints. Optimization Methods and Software, 2017, 32 (4), pp.892-903. ⟨10.1080/10556788.2016.1230209⟩. ⟨hal-01369135⟩
347 View
278 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More