Optimization for Shipping Logistics Paths Based on Evolutionary Ant Colony Algorithm: Improvement and Application of Dual Population Mechanism
Abstract
To improve the efficiency of shipping logistics, reduce transportation costs, and minimize energy consumption, this study introduces a dual population mechanism to improve the conventional ant colony algorithm and applies it to optimizing shipping logistics paths. Firstly, the shipping logistics network is abstracted as a set of nodes and edges in graph theory, simplifying the complex logistics network structure and providing a framework and theoretical basis for subsequent ant colony algorithm applications. Then, objective functions are set from four aspects: minimizing logistics transportation expenses, minimizing logistics transportation time, minimizing carbon emissions, and maximizing path reliability to guide the algorithm in searching for the optimal solution. Finally, a dual population mechanism is introduced, utilizing two independent ant populations for parallel search. Population 1 adopts an elite ant strategy to achieve fast convergence, while Population 2 uses an enhanced sub path evaluation mechanism to explore new solution spaces and help the population escape from local optima. By using the path contribution evaluation mechanism, better paths can be selected to obtain the optimal shipping logistics path. According to the simulation results, it can be seen that the total transportation time of this method is 41 days throughout the entire experimental cycle, saving 9 days and 7 days respectively compared to the two existing methods; The total transportation expenses of this method is 1250000 USD, saving 170000 USD and 130000 USD respectively compared to the two existing methods; The total carbon emissions of this method are 11800 tons, saving 1700 tons and 1400 tons respectively compared to the two existing methods. It can be seen that this method outperforms existing methods in terms of total transportation time, total transportation expenses and total carbon emissions, indicating that this method effectively achieves the design expectations.
DOI:
https://doi.org/10.31449/inf.v49i21.8415Downloads
Published
How to Cite
Issue
Section
License
I assign to Informatica, An International Journal of Computing and Informatics ("Journal") the copyright in the manuscript identified above and any additional material (figures, tables, illustrations, software or other information intended for publication) submitted as part of or as a supplement to the manuscript ("Paper") in all forms and media throughout the world, in all languages, for the full term of copyright, effective when and if the article is accepted for publication. This transfer includes the right to reproduce and/or to distribute the Paper to other journals or digital libraries in electronic and online forms and systems.
I understand that I retain the rights to use the pre-prints, off-prints, accepted manuscript and published journal Paper for personal use, scholarly purposes and internal institutional use.
In certain cases, I can ask for retaining the publishing rights of the Paper. The Journal can permit or deny the request for publishing rights, to which I fully agree.
I declare that the submitted Paper is original, has been written by the stated authors and has not been published elsewhere nor is currently being considered for publication by any other journal and will not be submitted for such review while under review by this Journal. The Paper contains no material that violates proprietary rights of any other person or entity. I have obtained written permission from copyright owners for any excerpts from copyrighted works that are included and have credited the sources in my article. I have informed the co-author(s) of the terms of this publishing agreement.
Copyright © Slovenian Society Informatika
