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

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

doi:10.1145/3319619.3322030

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 proceeding › Published conference contribution

3 Citations (Scopus)

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 language	English
Title of host publication	GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion
Editors	Manuel López-Ibáñez, Anne Auger, Thomas Stützle
Place of Publication	New York, USA
Publisher	ACM
Pages	195-196
Number of pages	2
ISBN (Electronic)	9781450367486
ISBN (Print)	9781450367486
DOIs	https://doi.org/10.1145/3319619.3322030
Publication status	Published - 13 Jul 2019
Event	The Genetic and Evolutionary Computation Conference GECCO 2019 - Prague, Czech Republic Duration: 13 Jul 2019 → 17 Jul 2019

Conference

Conference	The Genetic and Evolutionary Computation Conference GECCO 2019
Country/Territory	Czech Republic
City	Prague
Period	13/07/19 → 17/07/19

Bibliographical 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).

Keywords

Physarum
Competition
DMOO
2D Hexagonal grid
Diffusion

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Cite this

Awad, A., Usman, M., Lusseau, D., Coghill, G. M., & Pang, W. (2019). A Physarum-Inspired Competition Algorithm for Solving Discrete Multi-Objective Optimization Problems. In M. López-Ibáñez, A. Auger, & T. Stützle (Eds.), GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion (pp. 195-196). 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 et al.
GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion. ed. / Manuel López-Ibáñez; Anne Auger; Thomas Stützle. New York, USA: ACM, 2019. p. 195-196.

Research output: Chapter in Book/Report/Conference proceeding › Published conference 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 M López-Ibáñez, A Auger & T Stützle (eds), GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion. ACM, New York, USA, pp. 195-196, 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 López-Ibáñez M, Auger A, Stützle T, editors, GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion. New York, USA: ACM. 2019. p. 195-196 doi: 10.1145/3319619.3322030

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

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Keywords

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