[1]王静,邹静静,汪勇.考虑转运的应急物资两阶段优化调度[J].计算机技术与发展,2025,(04):37-44.[doi:10.20165/j.cnki.ISSN1673-629X.2024.0365]
　WANG Jing,ZOU Jing-jing,WANG Yong.Optimized Two-phase Emergency Material Scheduling Considering Transfer[J].,2025,(04):37-44.[doi:10.20165/j.cnki.ISSN1673-629X.2024.0365]
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考虑转运的应急物资两阶段优化调度()

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2025年04期
页码:
37-44
栏目:
软件技术与工程
出版日期:
2025-04-10

文章信息/Info

Title:
Optimized Two-phase Emergency Material Scheduling Considering Transfer
文章编号:
1673-629X(2025)04-0037-08
作者:
王静; 邹静静; 汪勇
武汉科技大学 管理学院,湖北 武汉 430081
Author(s):
WANG Jing; ZOU Jing-jing; WANG Yong
School of Management,Wuhan University of Science and Technology,Wuhan 430081,China
关键词:
物资调度; 双目标整数规划; 进化学习算法; 映射编码; 横向转运
Keywords:
material scheduling; bi-objective integer programming; evolutionary learning algorithm; mapping encoding; horizontal trans-fer
分类号:
TP301.6;F251
DOI:
10.20165/j.cnki.ISSN1673-629X.2024.0365
摘要:
供应物资受限下多供应点、多需求点、多种类的应急物资调度需要保障配送高效的同时提升各需求点的满足度。因此,通过建立以运输成本和需求满足度为目标的调度模型,设计进化学习算法(ELA)提升模型的求解效果和精度,给出高效的调度方案,引入转运点进一步降低各需求点的运输成本从而优化调度方案。 实验分析表明,第一阶段提出的决策变量映射编码避免产生无效的分配方案加快了求解速度,设计的 ELA 算法能较大程度地降低运输成本并提高需求满足度,与传统 GSA 相比,给出的调度方案使得运输成本降低 13. 6% ,需求满足度提高 18. 4% 。 第二阶段运用节约法优化后,双目标调度方案中将调度方案的运输成本再降低 11. 1% 。 结合实际调度需求,给出的两种方案中双目标调度方案适用于降低运输成本的实际需求,而最大需求满足度方案则对提升需求满足度更有帮助,两种方案为实际调度需求提供了更有价值的参考意义。
Abstract:
Under the constraint of supplying materials, the dispatching of emergency materials with multiple supply points, multiple demand points,and multiple types needs to guarantee the high efficiency of distribution and improve the satisfaction degree of each demand point at the same time. Therefore,by establishing a scheduling model with transportation cost and demand satisfaction as the ob-jectives,we design an evolutionary learning algorithm ( ELA) to improve the model’s solution effect and accuracy,give an efficient scheduling plan,and introduce transshipment points to further reduce the transportation cost of each demand point so as to optimize the scheduling plan. The experimental analysis shows that the decision variable mapping encoding proposed in the first stage accelerates the solution speed by avoiding the generation of ineffective allocation schemes,and the designed ELA can reduce the transportation cost and improve the degree of demand satisfaction to a larger extent,and the given scheduling scheme reduces the transportation cost by 13. 6% and improves the degree of demand satisfaction by 18. 4% compared with the traditional GSA. In the second stage,after optimization using the savings method,the transportation cost of the scheduling plan is further reduced by 11. 1% in the bi-objective scheduling plan.Combined with the actual scheduling demand,the two given schemes,the dual-objective scheduling scheme is suitable for the actual demand of reducing transportation cost, while the maximum demand satisfaction scheme is more helpful for improving the demand satisfaction,and the two schemes provide more valuable references for the actual scheduling demand.
更新日期/Last Update: 2025-04-10