20192019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)Requires access

A Dynamic Path Planning Model Based on K-means Algorithm and Simulated Annealing Algorithm

Tongliang Lu, Jiangtao Fu, Xichun Hu

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Abstract

Aiming at the problem that it is difficult to reduce logistics distribution cost through quantitative analysis, the paper takes the lowest logistics and transportation cost as objective function, comprehensively considers the location of logistics distribution centers, and constructs dynamic path planning model based on K-means algorithm and simulated annealing algorithm. Through simulation analysis, it can be found that by wisely selecting logistics distribution centers as transit service stations, the logistics distribution cost can be effectively reduced.

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What this paper is about

Aiming at the problem that it is difficult to reduce logistics distribution cost through quantitative analysis, the paper takes the lowest logistics and transportation cost as objective function, comprehensively considers the location of logistics distribution centers, and constructs dynamic path planning model based on K-means algorithm and simulated annealing algorithm. Through simulation analysis, it can be found that by wisely selecting logistics distribution centers as transit service stations, the logistics distribution cost can be effectively reduced.

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OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Aiming at the problem that it is difficult to reduce logistics distribution cost through quantitative analysis, the paper takes the lowest logistics and transportation cost as objective function, comprehensively considers the location of logistics distribution centers, and constructs dynamic path planning model based on K-means algorithm and simulated annealing algorithm. Through simulation analysis, it can be found that by wisely selecting logistics distribution centers as transit service stations, the logistics distribution cost can be effectively reduced.

Key concepts: Simulated annealing, Algorithm, Computer science, Motion planning, Path (computing), Mathematical optimization, Adaptive simulated annealing, Mathematics

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