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Multi-agent-Based Ant Colony Approach for Supply Chain Delivery Routing Problem

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Advances in Industrial and Production Engineering (FLAME 2022)

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

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Abstract

In the prospect of improving supply chain delivery planning, this paper introduces an improved vehicle routing model using the Ant colony optimization approach. Based on literature surveys, many related articles on VRP (vehicle routing problem) models proved suitable results exclusively in the hunt for an optimal delivery tour. The use of Ant colony optimization aid to ameliorate the supply chain delivery process by finding the best shortest route tour for consumers’ packet delivery to all locations. Ant colony optimization is an AI (Artificial Intelligence) technique that is based on a Metaheuristics approach with the main goal of effectively piloting through plausible road path selection using multi-Ant agents and appreciably scaling down the time aspect in the search of a fast and efficient delivery tour mission. Ant colony approach enables efficiency for the best routing selection process and time-saving while maximizing profit. For this study, a typical scenario of a supply chain delivery planning problem is assumed to illustrate the application of Ant colony optimization technique, and an efficient routing path selection is found after the computation of the model for both scenarios (from depart to return), and the total distance covered is minimal. Furthermore, graphical representations will be showcased for the problem scenario, the theoretical analysis and model formulation of Ant colony optimization are also explained, and a step-by-step Ant colony algorithm steps wise approach are described, and also other illustrations are well exhibited in below sections.

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Authors and Affiliations

  1. Department of Information Technology, Amity Institute of Information Technology, Amity University Uttar Pradesh, Noida, India

    Itoua Wanck Eyika Gaida

  2. Department of Mathematics, Amity Institute of Applied Sciences, Amity University Uttar Pradesh, Noida, India

    Mandeep Mittal

  3. Department of Mathematics, SRM Institute of Science and Technology, Delhi NCR Campus, Modinagar, Ghaziabad, Uttar Pradesh, India

    Ajay Singh Yadav

Authors
  1. Itoua Wanck Eyika Gaida
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  2. Mandeep Mittal
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  3. Ajay Singh Yadav
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Corresponding author

Correspondence to Mandeep Mittal .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Amity School of Engineering and Technology, Amity University, Noida, Uttar Pradesh, India

    Rakesh Kumar Phanden

  2. Department of Mechanical Engineering, Amity School of Engineering and Technology, Amity University, Noida, India

    Ravinder Kumar

  3. Department of Mechanical Engineering, Indian Institute of Technology Delhi, New Delhi, India

    Pulak Mohan Pandey

  4. Engineering Project Management School of Engineering, IT and Physical Sciences, Federation University Australia, Ballarat, VIC, Australia

    Ayon Chakraborty

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Data Availability

Data used for the distance values in the road map scenario are surmised for the purpose of testing the model on near realistic scenarios and showcase the ability and effectiveness to deliver satisfactory outcomes as applied.

Conflict of Interest

The Author(s) declare(s) that there is no conflict of interest.

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Gaida, I.W.E., Mittal, M., Yadav, A.S. (2023). Multi-agent-Based Ant Colony Approach for Supply Chain Delivery Routing Problem. In: Phanden, R.K., Kumar, R., Pandey, P.M., Chakraborty, A. (eds) Advances in Industrial and Production Engineering. FLAME 2022. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-1328-2_13

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  • DOI: https://doi.org/10.1007/978-981-99-1328-2_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-1327-5

  • Online ISBN: 978-981-99-1328-2

  • eBook Packages: EngineeringEngineering (R0)

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