five

"Dataset of tracking customer requests"

收藏
DataCite Commons2026-03-18 更新2026-05-03 收录
下载链接:
https://ieee-dataport.org/documents/dataset-tracking-customer-requests
下载链接
链接失效反馈
官方服务:
资源简介:
"Supply Chain Networks Distribution (SCND) topology aims to \u00afnd the best position and size for facilities to ensure optimal products \u00b0ow based on the Matheuristic approach (i.e. decomposition meta-heuristics). This problem is a multi-objective function designed to reduce the transportation costs and associated delivery times. The Matheuristic presents a brilliant hybridize between the meta-heuristics steps and mathematical procedures in solving large-size problems with the slightest deviation ;. This paper proposed an ant colony-based algorithm evolved by mathematical procedures called Mat-ACO, compared with SA \\simulated annealing\" and CA \\Camel algorithm.\" The authors deduced that the mathematical solution is limited as the instances grow, signi\u00afcantly if increased than 600 network hotspots. The Mat-ACO, SA, and CA results are close to counterparts obtained by LINGO, with a di\u00aeerence of 2.03%, 2.49%, and 3.75%, respectively, and continue to extract results from more than 1350 network hotspots. Themain contribution is to \u00afnd the optimum tuning parameters, which will reduce the deviation from the exact solution. This paper shows that no feasible solution can catch the LINGO in large-scale problems. At the same time, the CA is superior to SA in the large problem sizes, whileMat-ACO still presents preferred solutions in minimum time. The proposed methodology is classified as a closed-loop network strategy that targets green management"
提供机构:
IEEE DataPort
创建时间:
2026-03-18
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作