Kazbek R., Sergaziyev M., Kenzhe D., Raissov A., Yedilkhan D.
A Comparative Analysis of Crossovers in Genetic Algorithms for Route Optimization: Case Studies from Astana and Shymkent, Kazakhstan // Scientific Reports. — 2026. — Vol. 16. — Article No. 13816. — DOI: 10.1038/s41598-026-43898-7.

Abstract: The computation of optimal routes considering multiple factors is a key challenge in operations research with significant practical implications for real-world transport efficiency. Optimal bus transit routes require balancing time, cost, fuel consumption, and vehicle amortization. In such constrained urban routing problems, the impact of genetic algorithm (GA) crossover operators remains insufficiently explored, particularly for Path-TSP formulations derived from existing bus transit networks. This paper presents a comparative analysis of a genetic algorithm employing different crossover methods. The proposed approach is applied to optimize bus transit routes for key destinations within urban areas. The framework is validated using real-world datasets from Astana and Shymkent, Kazakhstan. Experimental results demonstrate strong performance in terms of runtime efficiency, number of feasible solutions generated, and frequency of recovering optimal routes, showing competitiveness with existing methods in the literature.

Link / DOI: https://doi.org/10.1038/s41598-026-43898-7