Work stealing with private integer-vector-matrix data structure for multi-core branch-and-bound algorithms

Summary In this paper, the focus is put on multi‐core branch‐and‐bound algorithms for solving large‐scale permutation‐based optimization problems. We investigate five work stealing (WS) strategies with a new data structure called integer–vector–matrix (IVM). In these strategies, each thread has a pr...

Full description

Saved in:
Bibliographic Details
Published inConcurrency and computation Vol. 28; no. 18; pp. 4463 - 4484
Main Authors Gmys, Jan, Leroy, Rudi, Mezmaz, Mohand, Melab, Nouredine, Tuyttens, Daniel
Format Journal Article
LanguageEnglish
Published Blackwell Publishing Ltd 25.12.2016
Wiley
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Summary In this paper, the focus is put on multi‐core branch‐and‐bound algorithms for solving large‐scale permutation‐based optimization problems. We investigate five work stealing (WS) strategies with a new data structure called integer–vector–matrix (IVM). In these strategies, each thread has a private IVM allowing the local management of a set of subproblems enumerated using a factorial system. The WS strategies differ in the way the victim thread is selected and the granularity of stolen work units (intervals of factoradics). To assess the efficiency of the private IVM‐based WS approach, the five WS strategies have been extensively experimented on the flowshop scheduling permutation problem and compared with their conventional linked‐list‐based counterparts. The obtained results demonstrate that the IVM‐based WS outperforms the linked‐list‐based one in terms of CPU time, memory usage and number of performed WS operations. Copyright © 2016 John Wiley & Sons, Ltd.
Bibliography:istex:9E250089F5C2BB80675CC8919EA05125E96614FA
ark:/67375/WNG-0FCM023J-G
ArticleID:CPE3771
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1532-0626
1532-0634
DOI:10.1002/cpe.3771