Improving a Lagrangian decomposition for the unconstrained binary quadratic programming problem

This paper presents a new alternative of Lagrangian decomposition based on column generation technique to solve the unconstrained binary quadratic programming problem. We use a mixed binary linear version of the original quadratic problem with constraints represented by a graph. This graph is partit...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Computers & operations research Ročník 39; číslo 7; s. 1577 - 1581
Hlavní autoři: Mauri, Geraldo Regis, Lorena, Luiz Antonio Nogueira
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Elsevier Ltd 01.07.2012
Elsevier
Pergamon Press Inc
Témata:
Clusters
Column generation
Decomposition
Forming
Graph theory
Graphs
Lagrange multiplier
Lagrangian decomposition
Mathematical analysis
Mathematical models
Operations research
Quadratic programming
Studies
Quadratic programming
Lagrangian decomposition
Column generation
ISSN:0305-0548, 1873-765X, 0305-0548
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:This paper presents a new alternative of Lagrangian decomposition based on column generation technique to solve the unconstrained binary quadratic programming problem. We use a mixed binary linear version of the original quadratic problem with constraints represented by a graph. This graph is partitioned into clusters of vertices forming subproblems whose solutions use the dual variables obtained by a coordinator problem. Computational experiments consider a set of difficult instances and the results are compared against other methods reported recently in the literature.
Bibliografie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-2
content type line 23
ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2011.09.008