A Physarum-Inspired Competition Algorithm for Solving Discrete Multi-Objective Optimization Problems

Abubakr Awad, Muhammad Usman, David Lusseau, George M. Coghill, Wei Pang

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

Abstract

Many real-world problems can be naturally formulated as discrete multi-objective optimization (DMOO) problems. In this research we propose a novel bio-inspired Physarum competition algorithm (PCA) to tackle DMOO problems by modelling the Physarum discrete motility over a hexagonal cellular automaton. Our algorithm is based on the chemo-attraction forces towards food resources
(Objective Functions) and the repulsion negative forces between the competing Physarum. Numerical experimental work clearly demonstrated that our PCA algorithm had the best performance for the spread indicator against three state-of-the-art evolutionary algorithms, and its effectiveness in terms of commonly used metrics. These results have indicated the superiority of PCA in exploring
the search space and keeping diversity, this makes PCA a promising algorithm for solving DMOO problems.
Original languageEnglish
Title of host publicationGenetic and Evolutionary Computation Conference Companion (GECCO ’19 Companion), July 13–17, 2019, Prague, Czech Republic
Place of PublicationNew York, USA
PublisherACM
ISBN (Print)9781450367486
DOIs
Publication statusAccepted/In press - 22 Mar 2019
EventThe Genetic and Evolutionary Computation Conference GECCO 2019 - Prague, Czech Republic
Duration: 13 Jul 201917 Jul 2019

Conference

ConferenceThe Genetic and Evolutionary Computation Conference GECCO 2019
CountryCzech Republic
CityPrague
Period13/07/1917/07/19

Fingerprint

Multiobjective optimization
Cellular automata
Evolutionary algorithms

Keywords

  • Physarum
  • Competition
  • DMOO
  • 2D Hexagonal grid
  • Diffusion

Cite this

Awad, A., Usman, M., Lusseau, D., Coghill, G. M., & Pang, W. (Accepted/In press). A Physarum-Inspired Competition Algorithm for Solving Discrete Multi-Objective Optimization Problems. In Genetic and Evolutionary Computation Conference Companion (GECCO ’19 Companion), July 13–17, 2019, Prague, Czech Republic New York, USA: ACM. https://doi.org/10.1145/3319619.3322030

A Physarum-Inspired Competition Algorithm for Solving Discrete Multi-Objective Optimization Problems. / Awad, Abubakr; Usman, Muhammad; Lusseau, David; Coghill, George M.; Pang, Wei.

Genetic and Evolutionary Computation Conference Companion (GECCO ’19 Companion), July 13–17, 2019, Prague, Czech Republic. New York, USA : ACM, 2019.

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

Awad, A, Usman, M, Lusseau, D, Coghill, GM & Pang, W 2019, A Physarum-Inspired Competition Algorithm for Solving Discrete Multi-Objective Optimization Problems. in Genetic and Evolutionary Computation Conference Companion (GECCO ’19 Companion), July 13–17, 2019, Prague, Czech Republic. ACM, New York, USA, The Genetic and Evolutionary Computation Conference GECCO 2019, Prague, Czech Republic, 13/07/19. https://doi.org/10.1145/3319619.3322030
Awad A, Usman M, Lusseau D, Coghill GM, Pang W. A Physarum-Inspired Competition Algorithm for Solving Discrete Multi-Objective Optimization Problems. In Genetic and Evolutionary Computation Conference Companion (GECCO ’19 Companion), July 13–17, 2019, Prague, Czech Republic. New York, USA: ACM. 2019 https://doi.org/10.1145/3319619.3322030
Awad, Abubakr ; Usman, Muhammad ; Lusseau, David ; Coghill, George M. ; Pang, Wei. / A Physarum-Inspired Competition Algorithm for Solving Discrete Multi-Objective Optimization Problems. Genetic and Evolutionary Computation Conference Companion (GECCO ’19 Companion), July 13–17, 2019, Prague, Czech Republic. New York, USA : ACM, 2019.
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author = "Abubakr Awad and Muhammad Usman and David Lusseau and Coghill, {George M.} and Wei Pang",
note = "Abubakr Awad and Muhammad Usman are supported by Elphinstone PhD Scholarship (University of Aberdeen). Wei Pang, David Lusseau and George M. Coghill are supported by the Royal Society International Exchange program (Grant Ref IE160806).",
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