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Solving Dial-A-Ride Problems Using Multiple Ant Colony System with Fleet Size Minimisation

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Advances in Computational Intelligence Systems (UKCI 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 650))

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Abstract

This paper proposes an ant colony optimization (ACO) based algorithm to minimise the fleet size required to solve dial-a-ride problem (DARP). In this work, a static multi-vehicle case of DARP is considered where routes of multiple vehicles are designed to serve customer requests which are known a priori. DARP necessitates the need of high quality algorithm to provide optimal feasible solutions. We employ an improved ACO algorithm called ant colony system (ACS) to solve DARP. The fleet minimisation is also achieved by using ACS. In summary, multiple ACS are employed to minimise the fleet size while generating feasible solutions for DARP. Furthermore, the theoretical results are also validated through simulations.

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Authors and Affiliations

  1. Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore

    Twinkle Tripathy, Sarat Chandra Nagavarapu, Kaveh Azizian, Ramesh Ramasamy Pandi & Justin Dauwels

Authors
  1. Twinkle Tripathy
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  2. Sarat Chandra Nagavarapu
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  3. Kaveh Azizian
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  4. Ramesh Ramasamy Pandi
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  5. Justin Dauwels
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Corresponding author

Correspondence to Justin Dauwels .

Editor information

Editors and Affiliations

  1. Xiamen University, Xiamen Shi, Fujian, China

    Fei Chao

  2. Cardiff University, Cardiff, United Kingdom

    Steven Schockaert

  3. Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong

    Qingfu Zhang

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Tripathy, T., Nagavarapu, S.C., Azizian, K., Ramasamy Pandi, R., Dauwels, J. (2018). Solving Dial-A-Ride Problems Using Multiple Ant Colony System with Fleet Size Minimisation. In: Chao, F., Schockaert, S., Zhang, Q. (eds) Advances in Computational Intelligence Systems. UKCI 2017. Advances in Intelligent Systems and Computing, vol 650. Springer, Cham. https://doi.org/10.1007/978-3-319-66939-7_28

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  • DOI: https://doi.org/10.1007/978-3-319-66939-7_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66938-0

  • Online ISBN: 978-3-319-66939-7

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