Parallel Beam Search for Combinatorial Optimization (Extended Abstract)

Inspired by the recent success of parallelized exact methods to solve difficult scheduling problems, we present preliminary results of a general parallel beam search framework for combinatorial optimization problems. Beam search is a constructive metaheuristic traversing a search tree layer by layer...

Full description

Saved in:
Bibliographic Details
Published inProceedings of the International Symposium on Combinatorial Search Vol. 15; no. 1; pp. 273 - 275
Main Authors Frohner, Nikolaus, Gmys, Jan, Melab, Nouredine, Raidl, Günther R., Talbi, El-ghazali
Format Journal Article
LanguageEnglish
Published 17.07.2022
Online AccessGet full text
ISSN2832-9171
2832-9163
2832-9163
DOI10.1609/socs.v15i1.21783

Cover

More Information
Summary:Inspired by the recent success of parallelized exact methods to solve difficult scheduling problems, we present preliminary results of a general parallel beam search framework for combinatorial optimization problems. Beam search is a constructive metaheuristic traversing a search tree layer by layer while keeping in each layer a bounded number of promising nodes to consider many partial solutions in parallel. We propose a variant which is suitable for intra-node parallelization by multithreading with data parallelism. For sufficiently large problem instances and beam widths our work-in-progress implementation in the JIT-compiled Julia language admits promising speed-ups over 30x on 32 cores with uniform memory access for the Permutation Flow Shop Scheduling (PFSP) problem with flowtime objective.
ISSN:2832-9171
2832-9163
2832-9163
DOI:10.1609/socs.v15i1.21783