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A Hybrid Model based on Genetic Algorithm and Space-Filling Curve applied to Optimization of Vehicle Routes

机译:基于遗传算法和空间填充曲线的混合模型在车辆路径优化中的应用

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This work is the result of a real problem in the Sanitation Company of Espirito Santo (Companhia Espirito Santense de Saneamento), which owns a Geographic Information System, but lacks a mechanism to build routes to server customers that open in average 2148 services requests per day. Therefore, we propose a Hybrid Optimization Algorithm that combines Genetic Algorithm and Space-Filling Curves to solve the Vehicle Route Problem. We establish the validity of the hybrid algorithm by performing tests in two different benchmarks datasets. Our proposal reached an average result of 12.7 percent and 4.1 percent better than the previous solutions in the first and second datasets respectively. Also, we compare our solution and five other variations of Ant Colony Optimization Algorithm. The results show that our proposal is superior in some simulations and, when it was not superior, presented the second-best results for almost all instances.
机译:这项工作是Espirito Santo卫生公司(Companhia Espirito Santense de Saneamento)的一个实际问题的结果,该公司拥有一个地理信息系统,但是缺乏建立通往服务器客户的路由的机制,该服务器每天平均会处理2148个服务请求。因此,我们提出了一种混合优化算法,将遗传算法和空间填充曲线相结合来解决车辆路径问题。我们通过在两个不同的基准数据集中执行测试来建立混合算法的有效性。我们的建议分别比第一和第二个数据集中的先前解决方案分别提高了12.7%和4.1%的平均结果。此外,我们比较了我们的解决方案和蚁群优化算法的其他五个变体。结果表明,我们的建议在某些模拟中是优越的,而当它不是优越时,则几乎在所有情况下都表现出次优的结果。

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