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Efficiency of parallel metaheuristics for solving combinatorial problems

Published: 14 June 2007 Publication History

Abstract

The paper investigates the speedup and quality of solution of parallel metaheuristics on multicomputer platform for the case studies of parallel genetic computation for solving the TSP and solving the room assignment problem by parallel simulated annealing. Parallel computational models have been suggested for solving the TSP by genetic approach with chromosome migration (SPMD paradigm) and for solving the room assignment problem by simulated annealing (manager/workers paradigm). The experimental study is based on flat (MPI-based) parallel program implementations on multicomputer platform. Performance and scalability analysis have been made in respect to the application size and multicomputer size. The impact of various factors on the quality of solutions have been investigated and presented.

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Cited By

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  • (2020)Exploiting Heterogeneous Parallelism on Hybrid Metaheuristics for Vector Autoregression ModelsElectronics10.3390/electronics91117819:11(1781)Online publication date: 27-Oct-2020
  • (2018)Parallelism on Hybrid Metaheuristics for Vector Autoregression Models2018 International Conference on High Performance Computing & Simulation (HPCS)10.1109/HPCS.2018.00134(828-835)Online publication date: Jul-2018
  • (2011)Obtaining Simultaneous Equation Models through a Unified Shared-Memory Scheme of MetaheuristicsProceedings of the 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum10.1109/IPDPS.2011.359(1981-1988)Online publication date: 16-May-2011

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cover image ACM Other conferences
CompSysTech '07: Proceedings of the 2007 international conference on Computer systems and technologies
June 2007
761 pages
ISBN:9789549641509
DOI:10.1145/1330598
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 June 2007

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Author Tags

  1. combinatorial problems
  2. evolutionary computing
  3. optimization
  4. parallel computing
  5. parallel metaheuristics
  6. simulated annealing

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Overall Acceptance Rate 241 of 492 submissions, 49%

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Cited By

View all
  • (2020)Exploiting Heterogeneous Parallelism on Hybrid Metaheuristics for Vector Autoregression ModelsElectronics10.3390/electronics91117819:11(1781)Online publication date: 27-Oct-2020
  • (2018)Parallelism on Hybrid Metaheuristics for Vector Autoregression Models2018 International Conference on High Performance Computing & Simulation (HPCS)10.1109/HPCS.2018.00134(828-835)Online publication date: Jul-2018
  • (2011)Obtaining Simultaneous Equation Models through a Unified Shared-Memory Scheme of MetaheuristicsProceedings of the 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum10.1109/IPDPS.2011.359(1981-1988)Online publication date: 16-May-2011

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