Abstract

This paper presents a synchronized transfer strategy in which operators can schedule logistics vehicles among employees and arrange the transfer of commodities. The transfer time consists of the vehicle waiting time and commodity transition time. By adopting the strategy, logistics vehicles can visit fewer communities, resulting in savings in transportation cost under ensuring punctual delivery. An integer programming model based on a space-time-state network is proposed to describe the complex transfer process. To simplify the model, time window and vehicle capacity constraints are embedded into the network. The alternating direction method of multipliers (ADMM) is designed to solve the model. In the ADMM-based solution framework, the original model can be converted into a series of shortest-path searching subproblems and iteratively solved using a dynamic programming (DP) algorithm. Our computational results show that the proposed model and algorithm are efficient and competitive.

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