摘要
物流配送路径优化是物流系统设计的关键环节。针对物流配送路径问题复杂性和多约束性,提出一种改进的遗传算法——自适应免疫遗传算法(AIGA)。该算法利用一种新的免疫疫苗选择策略和免疫操作方法,使得优化过程随进化代数自适应改变,结合并列选择法对多目标物流配送路径进行优化,并给出了解决多目标物流配送路径问题的具体步骤。最后通过仿真验证,该算法的计算效率,收敛性都有明显的提高,验证了算法的实用性和有效性。
The vehicle routing problem（VRP） is the key of logistics system design.According to the complexity and multiple constraint of the vehicle routing problem,an improved genetic algorithm-adaptive immune genetic algorithm（AIGA） is put forward.The new algorithm introduces a new selection strategy vaccines and immunization methods of operation,makes the optimization process adaptive change with evolutionary algebra,and combines with parallel selection method to optimize multi-objective distribution path,and the specific steps were given for the delivery multi-objective optimization of logistics distributio.Simulation results show that the improved algorithm high computation efficiency,and fast convergence,which verifies the practicability and effectiveness of the algorithm.
出处
《科学技术与工程》
北大核心
2013年第3期762-765,共4页
Science Technology and Engineering
基金
2012年江苏省高校科研成果产业化推进项目(JHB2012-36)
江苏省高校自然科学基金(10KJD520008)资助
关键词
遗传算法
物流配送
车辆路径优化
genetic algorithm logistics distribution vehicle routing optimizing
