Tackling the Subset Sum Problem with Fixed Size using an Integer Representation Scheme

Victor Parque*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Addressing the subset sum problem is relevant to study resource management problems efficiently. In this paper, we study a new scheme to sample solutions for the subset sum problem based on swarm-based optimization algorithms with distinct forms of selection pressure, the balance of exploration-exploitation, the multimodality considerations, and a search space defined by numbers associated with subsets of fixed size. Our experiments show that it is feasible to find optimal subsets with few number of fitness evaluations, and that Particle Swarm Optimization with Fitness Euclidean Ratio converges faster to the global optima with zero variability over independent runs. Since the search space is one-dimensional and friendly to parallelization schemes, our work is potential to study further classes of combinatorial problems using swarm-based optimization algorithms and the representation based on numbers.

Original languageEnglish
Title of host publication2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1447-1453
Number of pages7
ISBN (Electronic)9781728183923
DOIs
Publication statusPublished - 2021
Event2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Virtual, Krakow, Poland
Duration: 2021 Jun 282021 Jul 1

Publication series

Name2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings

Conference

Conference2021 IEEE Congress on Evolutionary Computation, CEC 2021
Country/TerritoryPoland
CityVirtual, Krakow
Period21/6/2821/7/1

Keywords

  • Differential evolution
  • Experiments
  • Integer representation
  • Optimization
  • Particle swarm
  • Subset sum

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computational Mathematics

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