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Workshop on Engineering Applications

WEA 2019: Applied Computer Sciences in Engineering pp 190–201Cite as

Binary Optimisation with an Urban Pigeon-Inspired Swarm Algorithm

Part of the Communications in Computer and Information Science book series (CCIS,volume 1052)

Abstract

In this paper we introduce a metaheuristic for optimisation of discrete binary problems, derived from a recently proposed particle swarm algorithm inspired on the foraging behaviour of urban pigeons. The new variant of the algorithm is obtained by mapping the real–valued search space of the original version into a discrete binary–valued encoding. We illustrate the feasibility of the method on several binary benchmark problems and we study the impact of different running parameters such as problem dimension, population size and maximum number of evaluations. The potential of the method and possible extensions for improvement are also discussed.

Keywords

  • Metaheuristics
  • Particle Swarm Optimisation
  • Binary optimisation benchmarks

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Author information

Authors and Affiliations

  1. Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Sergio Rojas-Galeano

Authors
  1. Sergio Rojas-Galeano
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Correspondence to Sergio Rojas-Galeano .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Universidad Distrital Francisco José de Caldas, Bogotá, Colombia

    Juan Carlos Figueroa-García

  2. Universidad Antonio Nariño, Bogotá, Colombia

    Mario Duarte-González

  3. Universidad Antonio Nariño, Bogotá, Colombia

    Sebastián Jaramillo-Isaza

  4. Universidad del Rosario, Bogotá, Colombia

    Alvaro David Orjuela-Cañon

  5. Corporación Unificada Nacional CUN, Bogotá, Colombia

    Yesid Díaz-Gutierrez

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Rojas-Galeano, S. (2019). Binary Optimisation with an Urban Pigeon-Inspired Swarm Algorithm. In: Figueroa-García, J., Duarte-González, M., Jaramillo-Isaza, S., Orjuela-Cañon, A., Díaz-Gutierrez, Y. (eds) Applied Computer Sciences in Engineering. WEA 2019. Communications in Computer and Information Science, vol 1052. Springer, Cham. https://doi.org/10.1007/978-3-030-31019-6_17

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  • DOI: https://doi.org/10.1007/978-3-030-31019-6_17

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