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A Hybrid ACO Algorithm for Capacitated Vehicle Routing Problems

机译:一种用于电容车辆路由问题的混合ACO算法

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The Capacitated Vehicle Routing Problem (CVRP) is a well-known combinatorial optimization problem. The traditional ant colony optimization (ACO) method usually can only find a local optimum of the CVRP, and the simulated annealing (SA) method can help ACO get trapped out of the local optima to explore new solutions. Thus, combining the idea of ant colony optimization (ACO) and simulated annealing (SA), we propose a novel hybrid algorithm named SACO to solve the CVRP. In addition, inspired by decomposed ACO algorithms, we extend our algorithm into the decomposed version named DSACO to improve the solution quality and decrease the computational time. We test the standard benchmark problems on both of the proposed two algorithms SACO and DSACO, and make a comparison with other existing ACO-based algorithms. The computational results show the advantages of the proposed algorithms.
机译:电容车辆路由问题(CVRP)是一个众所周知的组合优化问题。传统的蚁群优化(ACO)方法通常只能找到CVRP的局部最佳,而模拟退火(SA)方法可以帮助ACO被困在本地Optima中以探索新的解决方案。因此,组合蚁群优化(ACO)和模拟退火(SA)的思想,我们提出了一种名为SACO的新型混合算法来解决CVRP。此外,通过分解的ACO算法启发,我们将算法扩展到名为DSACO的分解版本,以提高解决方案质量并降低计算时间。我们在提出的两个算法SACO和DSACO中测试标准基准问题,并与其他基于ACO的算法进行比较。计算结果显示了所提出的算法的优点。

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