Abstract
In this research paper, we address the Bi-objective Traveling Salesman Problem (BTSP), which involves minimizing two conflicting objectives: travel time and monetary cost. To tackle this problem, we propose a novel three-Phase Hybrid Evolutionary Algorithm (3PHEA) that combines the Lin-Kernighan Heuristic, an enhanced Non-Dominated Sorting Genetic Algorithm, and a Pareto Variable Neighborhood Search. We conduct a comparative study comparing our approach with three existing methods specifically designed for solving BTSP. Our evaluation includes 14 instances of varying degrees of difficulty and different sizes. To assess the performance of the algorithms, we employ multi-objective performance indicators. The results of our study demonstrate that 3PHEA outperforms the existing approaches by a significant margin. It achieves coverage of up to 80% of the true Pareto fronts, indicating its superiority in solving the BTSP.
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Dib, O. (2023). Three-Phase Hybrid Evolutionary Algorithm for the Bi-Objective Travelling Salesman Problem. In: El Ayachi, R., Fakir, M., Baslam, M. (eds) Business Intelligence. CBI 2023. Lecture Notes in Business Information Processing, vol 484 . Springer, Cham. https://doi.org/10.1007/978-3-031-37872-0_13
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