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ACORD: Ant Colony Optimization and BNF Grammar Rule Derivation

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Enjoying Natural Computing

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11270))

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Abstract

Ant Colony Systems have been widely employed in optimization issues primarily focused on path finding optimization, such as Travelling Salesman Problem. The first algorithm was aiming to search for an optimal path in a graph, based on the behavior of ants seeking a path between their colony and a source of food. Besides, ant colony optimization algorithms have been applied to many combinatorial optimization problems, ranging from quadratic assignment to protein folding or routing vehicles and a lot of derived methods have been adapted to dynamic problems in real variables, stochastic problems, multi-targets and parallel implementations. The main advantage lies in the choice of the edge to be explored, defined using the idea of pheromone. This article proposes the use of Ant Colony Systems to explore a Backus-Naur form grammar whose elements are solutions to a given problem. Similar studies, without using Ant Colonies, have been used to solve optimization problems, such as Grammatical Swarm (based on Particle Swarm Optimization) and Grammatical Evolution (based on Genetic Algorithms). Proposed algorithm opens the way to a new branch of research in Swarm Intelligence, which until now has been almost non-existent, using ant colony algorithms to solve problems described by a grammar. (All source code in R is available at https://github.com/fernando-demingo/ACORD-Algorithm).

This research has been partially supported by European project Regulation Study in the Adoption of the autonomous driving in the European Urban Nodes (AUTOCITS): INEA/CEF/TRAN/M2015/1143746. Action No: 2015-EU-TM-0243-S and by Spanish project Integración de Sistemas Cooperativos para Vehículos Autómos en Tráfico Compartido (CAV): TRA2016-78886-C3-3-R.

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Acknowledgments

History of all great works is to witness that no great work was ever done without either the active or passive support a person’s surrounding and one’s close quarters. We are highly thankful to our learned faculty, and friend, Mr. Mario Pérez Jiménez for his active guidance throughout these years.

Author information

Authors and Affiliations

  1. Departamento de Sistemas Informáticos, Escuela Técnica Superior de Ingeniería de Sistemas Informáticos, Universidad Politécnica de Madrid, Alan Turing sn, 28031, Madrid, Spain

    Luis Fernando de Mingo López & Nuria Gómez Blas

  2. Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Campus de Montegancedo, 28660, Boadilla del Monte, Madrid, Spain

    Juan Castellanos Peñuela

  3. Department of Computer Science, Troy University, University Avenue, Troy, AL, 36081, USA

    Alberto Arteta Albert

Authors
  1. Luis Fernando de Mingo López
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  2. Nuria Gómez Blas
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  3. Juan Castellanos Peñuela
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  4. Alberto Arteta Albert
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Corresponding author

Correspondence to Luis Fernando de Mingo López .

Editor information

Editors and Affiliations

  1. University of Seville, Sevilla, Spain

    Carmen Graciani

  2. University of Seville, Sevilla, Spain

    Agustín Riscos-Núñez

  3. Romanian Academy, Bucharest, Romania

    Gheorghe Păun

  4. Leiden University, Leiden, The Netherlands

    Grzegorz Rozenberg

  5. Turku Centre for Computer Science, Turku, Finland

    Arto Salomaa

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de Mingo López, L.F., Blas, N.G., Peñuela, J.C., Albert, A.A. (2018). ACORD: Ant Colony Optimization and BNF Grammar Rule Derivation. In: Graciani, C., Riscos-Núñez, A., Păun, G., Rozenberg, G., Salomaa, A. (eds) Enjoying Natural Computing. Lecture Notes in Computer Science(), vol 11270. Springer, Cham. https://doi.org/10.1007/978-3-030-00265-7_9

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