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     Advance Journal of Food Science and Technology


Modeling and Optimization of Food Cold-chain Intelligent Logistics Distribution Network

1Wuxue Jiang, 2Zhixiong Hu, 3Yan Liang and 1Yuqiang Chen
1Department of Computer Engineering, Dongguan Polytechnic, Dongguan 523808, China
2College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan 430023, China
3Department of Computer Engineering, Maoming Polytechnic, Maoming 525000, China
Advance Journal of Food Science and Technology  2015  8:573-578
http://dx.doi.org/10.19026/ajfst.7.1361  |  © The Author(s) 2015
Received: August ‎13, ‎2014  |  Accepted: ‎September ‎22, ‎2014  |  Published: March 15, 2015

Abstract

Aiming at improving the efficiency of food cold-chain logistics network, shortening the logistic time of food and reducing the logistics cost of food, this study analyzes the optimization strategy and various cost factors of the supply network of food cold chain and establishes and expands a kind of logistics network model adapting to the food cold-chain logistics. We use an improved genetic algorithm to solve the model and design an effective coding scheme, through the modified adaptive crossover probability and mutation probability, we integrate them into the elitism strategy, which has effectively avoided the prematurity of the algorithm and improved the operation efficiency of the algorithm. In the same instance, compared with the simple genetic algorithm, this study puts forward that the average running time and the average iteration number of the improved genetic algorithm have reduced nearly 50%, which has proved the feasibility and the effectiveness of the model and the algorithm.

Keywords:

Elitism strategy, food cold chain, genetic algorithm, logistics network,


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2042-4876
ISSN (Print):   2042-4868
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