遗传算法求解VRP的种群初始化改进

Improvement on Population Initialization of Genetic Algorithm Solution for VRP

传统的遗传算法求解VRP时,初始种群多半采取随机生成法形成染色体方案,以致于迭代开始就可能形成许多不可行的方案,要进行大量的计算后才能得到优化的方案,这在很大程度上降低了算法的运算效率.论文提出的遗传编码策略,对初始种群给予基于知识型启发策略,使得初始种群一开始就表现为一种较优的状态.

When traditional Genetic Algorithms （GA） was applied in VRP, most of the initial population generate the chromosome program by taking a random method, which leads to a lot of infeasible schemes in the beginning, and a great deal of calculations before obtaining an optimize one. This reduced the calculating efficiency of the algorithm to the great extent. The genetic coding strategy, proposed by the paper, gives initial population a knowledge-based heuristic strategy, which makes initial population a better performance at the very start.