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Soft Computing for Recognition Based on Biometrics pp 365–385Cite as

Comparative Analysis of Hybrid Techniques for an Ant Colony System Algorithm Applied to Solve a Real-World Transportation Problem

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 312))

Abstract

This work presents a comparison of hybrid techniques used to improve the Ant Colony System algorithm (ACS), which is applied to solve the well-known Vehicle Routing Problem (VRP). The Ant Colony System algorithm uses several techniques to get feasible solutions as learning, clustering and search strategies. They were tested with the dataset of Solomon to prove the performance of the Ant Colony System, solving the Vehicle Routing Problem with Time Windows and reaching an efficiency of 97% in traveled distance and 92% in used vehicles. It is presented a new focus to improve the performance of the basic ACS: learning for levels, which permits the improvement of the application of ACS solving a Routing-Scheduling-Loading Problem (RoSLoP) in a company case study. ACS was applied to optimize the delivery process of bottled products, which production and sale is the main activity of the company. RoSLoP was formulated through the well-known Vehicle Routing Problem (VRP) as a rich VRP variant, which uses a reduction method for the solution space to obtain the optimal solution. It permits the use in efficient way of computational resources, which, applied in heuristic algorithms reach an efficiency of 100% in the measurement of traveled distance and 83% in vehicles used solving real-world instances with learning for levels. This demonstrates the advantages of heuristic methods and intelligent techniques for solving optimization problems.

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Authors and Affiliations

  1. Instituto Tecnológico Ciudad Madero, 1o. de mayo s/n, 89440. Col. Los Mangos, Cd. Madero, México

    Juan Javier González-Barbosa, José Francisco Delgado-Orta, Laura Cruz-Reyes, Héctor Joaquín Fraire-Huacuja & Apolinar Ramirez-Saldivar

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  1. Juan Javier González-Barbosa
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  2. José Francisco Delgado-Orta
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  3. Laura Cruz-Reyes
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  4. Héctor Joaquín Fraire-Huacuja
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  5. Apolinar Ramirez-Saldivar
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Editor information

Editors and Affiliations

  1. Tijuana Institute of Technology, Chula Vista, USA

    Patricia Melin

  2. Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  3. University of Alberta, Edmonton, Canada

    Witold Pedrycz

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González-Barbosa, J.J., Delgado-Orta, J.F., Cruz-Reyes, L., Fraire-Huacuja, H.J., Ramirez-Saldivar, A. (2010). Comparative Analysis of Hybrid Techniques for an Ant Colony System Algorithm Applied to Solve a Real-World Transportation Problem. In: Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Soft Computing for Recognition Based on Biometrics. Studies in Computational Intelligence, vol 312. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15111-8_23

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  • DOI: https://doi.org/10.1007/978-3-642-15111-8_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15110-1

  • Online ISBN: 978-3-642-15111-8

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