Multi-objective path planning based on K-D fusion algorithm

Supeng Kong, Surong Chen*, Zhaoxi Zhong, Bin Xu, Tianlei Shi, Xiaohui Zhu, Yong Yue, Wei Wang

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)


How to arrange sales staff to visit offline stores reasonably is a critical task in the Fast Moving Consumer Goods (FMCG) industry. Based on the K-means and Dijkstra algorithms (KD fusion algorithm), this paper proposed an algorithm to automatically allocate offline stores for sales staff and optimize the visiting path, thereby improving management efficiency. A new initial cluster center selection approach was proposed for the K-means algorithm to select its initial clustering center with the consideration of outlier points. The sales staff's visiting path to the store was planned by the Dijkstra algorithm. The performance of our K-D fusion algorithm was evaluated in terms of grouping rationality and path planning optimization. Experimental results show that our algorithm can comprehensively consider several factors such as the number of stores, store types, and geographical locations, and distribute the workload more evenly to all the sales staff. In addition, it can also optimize the visiting path for sales staff, which can effectively improve the efficiency of sales staff to visit offline stores.

Original languageEnglish
Article number012037
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 4 Mar 2021
Event2020 International Symposium on Automation, Information and Computing, ISAIC 2020 - Beijing, Virtual, China
Duration: 2 Dec 20204 Dec 2020

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