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- W4387006055 abstract "The traveling salesman problem (TSP) is a classic NP-hard combinatorial optimization problem that has drawn extensive research endeavor due to its theoretical significance and a wide variety of applications. This paper proposes an improved genetic algorithm with two novel strategies. The first strategy uses a Euclidean geometry-based approach to construct an initial population of high-quality solutions through a greedy convex hull algorithm. This strategy helps to effectively reduce the search space and focus on promising regions. The second strategy is a hybrid heuristic crossover operator that combines a new recombination-insertion crossover with a well-known order crossover (OX). Our test results show that either strategy significantly enhances the performance of the classic GA. Moreover, combining both approaches demonstrates a strong synergistic effect for further improvements by outperforming several GA variants and a simulated annealing approach in terms of error rates and consistency of the results." @default.
- W4387006055 created "2023-09-26" @default.
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- W4387006055 date "2023-07-01" @default.
- W4387006055 modified "2023-09-26" @default.
- W4387006055 title "An Improved Genetic Algorithm With Euclidean Geometry and Hybrid Heuristic Crossover for Traveling Salesman Problem" @default.
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- W4387006055 doi "https://doi.org/10.1109/cec53210.2023.10254179" @default.
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