为做好集配一体化背景下物流网络选址-路径规划设计,用大规模邻域搜索算法的破坏、重组策略代替传统混合自适应遗传算法中的交叉、变异过程,实现算法的优化设计.通过模拟算例分析可知,优化后的算法能够有效克服传统算法在运算过程中出现的早熟及稳定性差等问题,在一定程度上提升获取更优解的概率,提高客户满意度.利用已知标杆数据对算法进行有效性检验.计算结果表明:优化后的算法各项指标表现良好,对于部分数据的计算结果优于其他3个已有算法,与已知最优解基本保持一致,进一步验证了优化算法的科学性和有效性.
In order to do a good job in the site selection-path planning and design of logistics network under the background of integration of simultaneous distribution and collection, the crossover and mutation processes in the traditional hybrid adaptive genetic algorithm are replaced by the destruction and recombination strategies of the large-scale neighborhood search algorithm, and the optimization design of the algorithm is realized.After analyzing the simulation example, it can be seen that the optimized algorithm can effectively overcome the problems of early maturity and poor stability of the traditional algorithm in the calculation process, improve the probability of obtaining a better solution to a certain extent, and improve customer satisfaction.The effectiveness of the algorithm is tested by using the known benchmark data, and the calculation results show that the indicators of the optimized algorithm perform well, and the calculation results of some data are better than the other three existing algorithms, which is basically consistent with the known optimal solution, and this further verifies the scientificity and effectiveness of the optimization algorithm in this paper.
[1] 黄凯明,卢才武,连民杰.三层级设施选址-路径规划问题建模及算法研究[J].系统工程理论与实践,2018,38(3):743-754. DOI: 10.12011/1000-6788(2018)03-0743-12.
[2] 汤杼彬.基于和声搜索算法的多层级物流中心 选址问题[J].物流技术,2019, 38(11): 89-92. DOI: 10.3969/j.issn.1005-152X.2019.11.019.
[3] 邹筱,张晓宁.准时达限制条件的冷链物流配送中心选址模型[J].统计与决策,2020, 36(12): 185-188. DOI: 10.13546/j.cnki.tjyjc.2020.12.041.
[4] 田立霞,黄元生,赵恒凤,等.均衡条件下加氢站的选址定容优化[J].河北大学学报(自然科学版), 2021, 41(3): 245-250. DOI: 10.3969/j.issn.1000-1565.2021.03.004.
[5] 韦子辉,李小阳,王勒,等.基于自适应Levy飞行改进的TDOA三维定位算法[J].河北大学学报(自然科学版), 2023, 43(2): 207-215. DOI: 10.3969/j.issn.1000-1565.2023.02.013.
[6] DANTZIG G B, RAMSER J H. The truck dispatching problem[J]. Manag Sci, 1959, 6(1): 80-91. DOI: 10.1287/mnsc.6.1.80.
[7] 马贵平,潘峰.基于改进蚁群算法的物流运输路径研究[J].计算机工程与科学, 2020, 42(3): 523-528. DOI: 10.3969/j.issn.1007-130X.2020.03.019.
[8] 濮明月,张彦如.基于改进蚁群算法的物流配送车辆路径优化方法[J].吉林化工学院学报, 2021, 38(5): 90-94. DOI: 10.16039/j.cnki.cn22-1249.2021.05.019.
[9] 夏强,周健勇.基于MATLAB软件的运输路径优化研究[J].物流科技, 2020, 43(10): 97-100. DOI: 10.13714/j.cnki.1002-3100.2020.10.024.
[10] 王祺,肖青.模糊需求下的多中心冷链配送车辆路径问题[J].计算机工程与应用, 2023, 59(23): 341-350. DOI: 10.3778/j.issn.1002-8331.2208-0143.
[11] MARANZANA F E. On the location of supply points to minimize transportation costs[J]. IBM Syst J, 2010, 2(2): 129-135. DOI: 10.1147/sj.22.0129.
[12] 王万良,朱文成,赵燕伟.基于全局边缘排序的超启发算法在绿色物流选址—路径优化问题中的应用[J].计算机集成制造系统, 2020, 26(4): 1097-1107. DOI: 10.13196/j.cims.2020.04.023.
[13] 刘凡,张惠珍,周迅.带模糊需求的开放式选址路径问题的混合离散蘑菇繁殖算法[J].计算机应用研究, 2021, 38(3): 738-744, 750. DOI: 10.19734/j.issn.1001-3695.2020.02.0023.
[14] 周迅,张惠珍.求解开放式选址路径问题的离散烟花算法[J].软件导刊, 2021, 20(3): 43-50. DOI: 10.11907/rjdk.202389.
[15] 张得志,张湘鹏,王润泽,等.基于两阶段的超大型城市物流网络选址与服务路径优化[J].铁道科学与工程学报, 2023, 20(4): 1270-1279. DOI: 10.19713/j.cnki.43-1423/u.t20220845.
[16] 陈丽萍,苑侗侗,杨文柱,等.基于模板更新的深层孪生网络跟踪算法[J].河北大学学报(自然科学版), 2022, 42(2): 217-224. DOI: 10.3969/j.issn.1000-1565.2022.02.016.
[17] 尹博然,马俊,陈博行,等.基于未覆盖顶点的无线传感器网络覆盖优化[J].河北大学学报(自然科学版), 2023, 43(5): 553-560. DOI: 10.3969/j.issn.1000-1565.2023.05.015.
[18] BARRETO S S. Analysis and modeling of Location-routing problems[D]. Aveiro:University of Averiro,Portugal,2004. (
