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Optimization of Routing Problem for Cold Chain Logistics Considering Customer Value

Published: 14 October 2022 Publication History

Abstract

There are some problems in urban cold chain logistics such as low timeliness and low customer value. This paper establishes the fresh cold chain logistics delivery routing optimization model with the minimum total cost and maximum potential customer value as the objective function, based on the perishable characteristics of fresh products and the customer value theory. The model considers vehicle load, mileage limit, and customer time window constraints. Then a hybrid genetic-simulated annealing algorithm is designed to solve the model, and an example is used to verify the effectiveness of the algorithm. In addition, the comparative analysis of the results obtained by the genetic algorithm and the genetic-simulated annealing algorithm shows that the latter can search for a better solution. The method proposed in this paper can maximize the value of customers and reduce the cost of delivery.

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ICCIR '22: Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics
June 2022
905 pages
ISBN:9781450397179
DOI:10.1145/3548608
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 14 October 2022

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