Research on Location Optimization of Low-Carbon Cold Chain Logistics Distribution Center by FWA-Artificial Fish Swarm Algorithm

2021 ◽  
Author(s):  
Mingyue Fu ◽  
Teng Fei ◽  
Liyi Zhang ◽  
Hongbo Li
Keyword(s):  
Distribution Center ◽  
Cold Chain ◽  
Low Carbon ◽  
Artificial Fish Swarm Algorithm ◽  
Location Optimization ◽  
Logistics Distribution ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm

scholarly journals Application of FWA-Artificial Fish Swarm Algorithm in the Location of Low-Carbon Cold Chain Logistics Distribution Center in Beijing-Tianjin-Hebei Metropolitan Area

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Liyi Zhang ◽  
Mingyue Fu ◽  
Teng Fei ◽  
Xuhua Pan
Keyword(s):  
Metropolitan Area ◽  
Carbon Emission ◽  
Time Window ◽  
Hot Spot ◽  
Cold Chain ◽  
Low Carbon ◽  
Fireworks Algorithm ◽  
Artificial Fish Swarm Algorithm ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm

Green development is the hot spot of cold chain logistics today. Therefore, this paper converts carbon emission into carbon emission cost, comprehensively considers cargo damage, refrigeration, carbon emission, time window, and other factors, and establishes the optimization model of location of low-carbon cold chain logistics in the Beijing-Tianjin-Hebei metropolitan area. Aiming at the problems of the fish swarm algorithm, this paper makes full use of the fireworks algorithm and proposes an improved fish swarm algorithm on the basis of the fireworks algorithm. By introducing the explosion, Gaussian mutation, mapping and selection operations of the fireworks algorithm, the local search ability and diversity of artificial fish are enhanced. Finally, the modified algorithm is applied to optimize the model, and the results show that the location scheme of low-carbon cold chain logistics in Beijing-Tianjin-Hebei metropolitan area with the lowest total cost can be obtained by using fireworks-artificial fish swarm algorithm.

Logistics Route Optimization Based on Improved Fish Swarm Algorithm

2015 ◽  
Vol 713-715 ◽  
pp. 1761-1764
Author(s):  
Feng Kai Xu
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Ant Colony Algorithm ◽  
Low Cost ◽  
Ant Colony ◽  
Route Optimization ◽  
Artificial Fish Swarm Algorithm ◽  
Logistics Distribution ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm

In order to achieve a low cost and low exhaust pollution in logistics distribution path. In view of the shortages of existing genetic algorithm and ant colony algorithm which have the characteristics of some limitations, such as ant colony algorithm's convergence slow, easy going, the characteristics of such as genetic algorithm premature convergence in the process of path optimization, process complex, the paper proposed the improved artificial fish swarm algorithm in order to solve logistics route optimization problem. At last, through simulation experiment, the improved artificial fish swarm algorithm is proved correct and effective.

PERFORMANCE EVALUATION OF CULTURAL ARTIFICIAL BEE COLONY AND CULTURAL ARTIFICIAL FISH SWARM ALGORITHM

2019 ◽  
Vol 6 (4) ◽  
pp. 43
Author(s):  
HADIR ADEBIYI BUSAYO ◽  
TIJANI SALAWUDEEN AHMED ◽  
FOLASHADE O. ADEBIYI RISIKAT ◽  
◽  
◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Artificial Bee Colony ◽  
Artificial Fish Swarm Algorithm ◽  
Bee Colony ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm
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