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Bee Inspired Novel Optimization Algorithm and Mathematical Model for Effective and Efficient Route Planning in
Kah Huo Leong1, Hamzah Abdul-Rahman1, Chen Wang2
1Faculty of Science Technology Engineering and Mathematics (STEM), International University of Malaya-Wales, Kuala Lumpur, Malaysia.
Plos One
|December 9, 2016
Summary
This study introduces a novel optimization algorithm inspired by bee foraging behavior to solve the Traveling Salesman Problem (TSP) for railway and metro transport systems (RS). The algorithm efficiently plans optimal routes, minimizing resources and time for complex urban transit networks.
Area of Science:
- Operations Research
- Transportation Engineering
- Computational Intelligence
Background:
- Urbanization and economic development increase demand for efficient urban rail transit (RS).
- Route optimization for multiple destinations in RS, a variant of the Traveling Salesman Problem (TSP), lacks universal solutions.
- Existing methods struggle with the complexity of real-world railway route planning.
Purpose of the Study:
- To develop an optimization algorithm for selecting optimal routes in railway and metro transport systems.
- To address the Traveling Salesman Problem (TSP) specifically within the context of urban rail transit.
- To enhance decision-making for business practitioners in railway route planning.
Main Methods:
- Algorithm development inspired by bee foraging behavior.
- Verification through comparison with exact solutions across 10 test cases.
- Demonstration of application using a large-scale numerical case study.
Main Results:
- The developed algorithm demonstrates efficiency and effectiveness in railway route planning.
- Optimal routes were completed within specified timeframes using minimal resources.
- The algorithm proved reliable for problems of varying complexity.
Conclusions:
- The bee-foraging-inspired algorithm offers a reliable solution for railway TSP.
- This method assists in making better business decisions for route planning in urban rail transit.
- The algorithm's effectiveness is validated for practical application in complex transportation networks.
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