CAJ | 학술논문

根据组合优化理论，充分利用遗传算法、蚁群算法的优化点，提出了一种两阶段式的物流配送路径优化方法（GA-ACO）。利用遗传算法迅速找到物流配送路径优化问题的初始解，初始解生成蚁群算法的初始信息素分布，通过蚁群算法找到物流配送路径的最优方案。采用实例对GA-ACO的性能进行测试，测试结果表明，GA-ACO可以获得较好的物流配送路径优化方案，是一种高效率、鲁棒性好的物流配送路径优化问题求解方法。
근거조합우화이론，충분이용유전산법、의군산법적우화점，제출료일충량계단식적물류배송로경우화방법（GA-ACO）。이용유전산법신속조도물류배송로경우화문제적초시해，초시해생성의군산법적초시신식소분포，통과의군산법조도물류배송로경적최우방안。채용실례대GA-ACO적성능진행측시，측시결과표명，GA-ACO가이획득교호적물류배송로경우화방안，시일충고효솔、로봉성호적물류배송로경우화문제구해방법。
According to the combination optimization theory and to make full use of optimization genetic algorithm and ant colony algorithm, this paper puts forward a novel method of logistics distribution route optimization based on genetic algorithm and ant colony optimization algorithm. The mathematical model of logistics distribution route optimization problem is established, and then genetic algorithm which has the global optimization search ability is used to find the fea-sible scheme of logistics distribution route, the feasible scheme of the genetic algorithm is taken as the initial solution of the ant colony algorithm, the behavior of ant foraging is simulated to find the optimal solution of logistics distribution route. The performance of the proposed method is tested by simulation experiments, test results show that the proposed method can obtain better optimization scheme of logistics distribution route, is a high efficiency and robustness optimiza-tion method to solve logistics distribution routing problem.