Scaling exact multi-objective combinatorial optimization by parallelization

  • Jianmei Guo*
  • , Edward Zulkoski
  • , Rafael Olaechea
  • , Derek Rayside
  • , Krzysztof Czarnecki
  • , Sven Apel
  • , Joanne M. Atlee
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

39 Scopus citations

Abstract

Multi-Objective Combinatorial Optimization (MOCO) is fundamental to the development and optimization of software systems. We propose five novel parallel algorithms for solving MOCO problems exactly and efficiently. Our algorithms rely on off-the-shelf solvers to search for exact Pareto-optimal solutions, and they parallelize the search via collaborative communication, divide-and-conquer, or both. We demonstrate the feasibility and performance of our algorithms by experiments on three case studies of software-system designs. A key finding is that one algorithm, which we call FS-GIA, achieves substantial (even super-linear) speedups that scale well up to 64 cores. Furthermore, we analyze the performance bottlenecks and opportunities of our parallel algorithms, which facilitates further research on exact, parallel MOCO.

Original languageEnglish
Title of host publicationASE 2014 - Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering
PublisherAssociation for Computing Machinery, Inc
Pages409-420
Number of pages12
ISBN (Electronic)9781450330138
DOIs
StatePublished - 2014
Externally publishedYes
Event29th ACM/IEEE International Conference on Automated Software Engineering, ASE 2014 - Vasteras, Sweden
Duration: 15 Sep 201419 Sep 2014

Publication series

NameASE 2014 - Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering

Conference

Conference29th ACM/IEEE International Conference on Automated Software Engineering, ASE 2014
Country/TerritorySweden
CityVasteras
Period15/09/1419/09/14

Keywords

  • Multi-objective combinatorial optimization
  • Parallelization

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