CAJ | 학술논문

遗传算法求解车辆路径问题时，优秀基因片段易被破坏，导致算法效率不高等问题，因此遗传算法在解决车辆路径问题时有一定的局限性。通过对该问题的深入分析，提出基于正向变异的遗传算法。控制变异的方向，尽量避免破坏优秀基因的同时大量破坏较差基因，得到更多较优的新基因片段。实验结果表明，该算法有效提高了遗传算法解决车辆路径问题的效率。
유전산법구해차량로경문제시，우수기인편단역피파배，도치산법효솔불고등문제，인차유전산법재해결차량로경문제시유일정적국한성。통과대해문제적심입분석，제출기우정향변이적유전산법。공제변이적방향，진량피면파배우수기인적동시대량파배교차기인，득도경다교우적신기인편단。실험결과표명，해산법유효제고료유전산법해결차량로경문제적효솔。
Crossover operation fails to keep good genes when using genetic algorithm to solve VRP problem ,which leads to prob‐lems including slower convergence .To a certain extent ,the usefulness of genetic algorithms to solve the VRP problem is affec‐ted .On the basis of predecessors ,a forward mutation method was created .Poor gene fragment connection was dismantled and new connection was created to get a better gene .Results of a large number of experiments show that the proposed method great‐ly improves the genetic algorithm on solving such problems efficiently .