Application on Cold Chain Logistics Routing Optimization Based on Improved Genetic Algorithm

2019 ◽  
Vol 53 (2) ◽  
pp. 169-180 ◽  
Author(s):  
Liyi Zhang ◽  
Yang Gao ◽  
Yunshan Sun ◽  
Teng Fei ◽  
Yujing Wang
Keyword(s):  
Genetic Algorithm ◽  
Cold Chain ◽  
Improved Genetic Algorithm ◽  
Routing Optimization

scholarly journals Erratum to: Application on Cold Chain Logistics Routing Optimization Based on Improved Genetic Algorithm

2019 ◽  
Vol 53 (6) ◽  
pp. 572-572
Author(s):  
Liyi Zhang ◽  
Yang Gao ◽  
Yunshan Sun ◽  
Teng Fei ◽  
Yujing Wang
Keyword(s):  
Genetic Algorithm ◽  
Cold Chain ◽  
Improved Genetic Algorithm ◽  
Routing Optimization

QoS Routing Optimization Based on Improved Genetic Algorithm

2014 ◽  
Vol 998-999 ◽  
pp. 1169-1173
Author(s):  
Chang Lin He ◽  
Yu Fen Li ◽  
Lei Zhang
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Computational Complexity ◽  
Fitness Function ◽  
Qos Routing ◽  
Experimental Results ◽  
Improved Genetic Algorithm ◽  
Coding Schemes ◽  
Routing Optimization

A improved genetic algorithm is proposed to QoS routing optimization. By improving coding schemes, fitness function designs, selection schemes, crossover schemes and variations, the proposed method can effectively reduce computational complexity and improve coding accuracy. Simulations are carried out to compare our algorithm with the traditional genetic algorithms. Experimental results show that our algorithm converges quickly and is reliable. Hence, our method vastly outperforms the traditional algorithms.

scholarly journals Selection of Cold Chain Logistics Distribution Center Location Based on Improved Genetic Algorithm

2018 ◽  
Vol 227 ◽  
pp. 02018
Author(s):  
Jianchang Lu ◽  
Yaxin Zhao
Keyword(s):  
Genetic Algorithm ◽  
Time Window ◽  
Rapid Development ◽  
Cold Chain ◽  
Distribution Model ◽  
Improved Genetic Algorithm ◽  
Actual Case ◽  
Logistics Industry ◽  
Penalty Cost ◽  
Logistics Distribution

With the rapid development of food refrigeration and freezing technology, food cryogenic storage and vehicle transportation scheduling technology, the cold chain logistics industry has entered a period of rapid development. According to the problem of urban cold chain distribution route, based on the vehicle distribution model with time window, the minimum cost of transportation, cost of energy, cost of goods, penalty cost is the objective function, and the urban cold chain logistics distribution path is established. Optimized mathematical model. According to the actual case, the analysis of the cold chain distribution model is carried out by using the analytical genetic algorithm, and the optimal combination of the distribution paths with the lowest total cost is obtained, which has certain reference significance for the urban cold chain logistics distribution route problem.

Research on the Route Optimization as to Timing Uncertainty of Wartime Transportation

2014 ◽  
Vol 556-562 ◽  
pp. 5328-5332
Author(s):  
Lin Zhu ◽  
Xiao Dun ◽  
Can Shi Zhu
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Traditional Method ◽  
Uncertain Parameter ◽  
Route Optimization ◽  
Objective Functions ◽  
Improved Genetic Algorithm ◽  
Routing Optimization ◽  
Timing Uncertainty ◽  
Pass Through

Affected with various factors in wartime, the time during which the transport vehicles of military supplies pass through a certain section of a route is an uncertain parameter, whose optimization objective functions and constraints cannot be defined and solved through the traditional method of deterministic planning. In response to the problem, a routing optimization model is put forward herein for the timing uncertainty of wartime transportation and a method is devised for the Improved Genetic Algorithm to solve the routing optimization model with respect to timing uncertainty. Examples are also cited to verify the rationality of the algorithm as well as the correctness of the model.

scholarly journals MULTI-OBJECTIVE DISTRIBUTION ROUTING OPTIMIZATION WITH TIME WINDOW BASED ON IMPROVED GENETIC ALGORITHM

2018 ◽  
Vol 48 (3) ◽  
pp. 151-156
Author(s):  
S. WU ◽  
C. CHEN
Keyword(s):  
Genetic Algorithm ◽  
Time Window ◽  
Time Windows ◽  
Optimal Solution ◽  
Transportation Cost ◽  
Population Diversity ◽  
Improved Genetic Algorithm ◽  
Routing Problem ◽  
Logistics Distribution ◽  
Routing Optimization

In order to solve the shortcomings of the traditional genetic algorithm in solving the problem of logistics distribution path, a modified genetic algorithm is proposed to solve the Vehicle Routing Problem with Time Windows (VRPTW) under the condition of vehicle load and time window. In the crossover process, the best genes can be preserved to reduce the inferior individuals resulting from the crossover, thus improving the convergence speed of the algorithm. A mutation operation is designed to ensure the population diversity of the algorithm, reduce the generation of infeasible solutions, and improve the global search ability of the algorithm. The algorithm is implemented on Matlab 2016a. The example shows that the improved genetic algorithm reduces the transportation cost by about 10% compared with the traditional genetic algorithm and can jump out of the local convergence and obtain the optimal solution, thus providing a more reasonable vehicle route.

scholarly journals Optimizing the transportation route of fresh food in cold chain logistics by improved genetic algorithms

2019 ◽  
Vol 10 ◽  
pp. 14
Author(s):  
Jing Peng
Keyword(s):  
Genetic Algorithm ◽  
Economic Benefits ◽  
Cold Chain ◽  
Improved Genetic Algorithm ◽  
Transport Efficiency ◽  
Stage Of Development ◽  
Fresh Food ◽  
Traditional Algorithm ◽  
Transport Path ◽  
Transportation Route

At present, fresh food logistics transportation in China is still in the primary stage of development, transportation costs are rising, and cold chain logistics path design is unreasonable. Therefore, the optimization and prediction of the cold chain transportation route of fresh food has become the focus of the research in this field. Based on the principle of genetic algorithm, this paper designs an improved genetic algorithm to solve the problem of urban cold chain transportation path. In order to optimize the distribution path and minimize the total cost, a cold chain transport model is established. Through the simulation coding and calculation of the model, the influence of genetic algorithm on the optimization of the cold chain transport path is explored to reduce the cost and price of cold chain logistics transport, improve the transport efficiency, and thus improve the economic benefits of enterprises in this field. Through experiments, the optimal solution of the example is obtained, and compared with the traditional algorithm, it is proved that all the paths obtained by the improved genetic algorithm conform to the model with capacity constraint and time window constraint, and there is an optimal path for the most energy saving. In conclusion, the transport path of cold chain logistics calculated by the improved genetic algorithm is more optimized than the traditional algorithm and greatly improves the transport efficiency.

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