改进的遗传算法在车辆路径问题中的应用

通过对车辆路径问题的深入分析，针对遗传算法中“种群多样性”和“选择压力”两个最重要因素，对“交叉算子”和“变异算子”进行了改进，并和一般的遗传算法进行了比较，通过计算结果证明：在算法性能方面，改进的算法收敛速度较快，所求得的最优解质量较高，且计算结果稳定；在车辆配送路径方面，改进算法得到四条最优配送路线，并且四条线路没有交叉，完全形成回路，又同时满足车辆满载率的限制，而一般的遗传算法得到五条配送路线，最低装载量仅为3．1t，并不能达到车辆相应的满载率，因此，改进的遗传算法明显优于传统的遗传算法．

Genetic Algorithms for Vehicle Routing Problem

Based on the vehicle routing problem in-depth analysis,and direct against the most important two factors of population diversity and pressure choosing,the main working is improved the main factors cross operator and mutation operator.And compared with the genetic algorithm,results of numerical tests show that:on one aspect of the vehicle routing:the algorithm has higher rate of convergence,more superior solution,and more stable of calculation result;on the anther aspect of the vehicle routing:the optimal de...