Research on the optimization algorithm of logistic unload container based on Hopfield neural network

Author(s):  
Xiaoyun Wang ◽  
Zhongming Zhang ◽  
Li Yang
2021 ◽  
Vol 1821 (1) ◽  
pp. 012038
Author(s):  
Mohd. Asyraf Mansor ◽  
Mohd Shareduwan Mohd Kasihmuddin ◽  
Saratha Sathasivam

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Yanxia Sun ◽  
Zenghui Wang ◽  
Barend Jacobus van Wyk

A new neural network based optimization algorithm is proposed. The presented model is a discrete-time, continuous-state Hopfield neural network and the states of the model are updated synchronously. The proposed algorithm combines the advantages of traditional PSO, chaos and Hopfield neural networks: particles learn from their own experience and the experiences of surrounding particles, their search behavior is ergodic, and convergence of the swarm is guaranteed. The effectiveness of the proposed approach is demonstrated using simulations and typical optimization problems.


2009 ◽  
Vol 29 (4) ◽  
pp. 1028-1031
Author(s):  
Wei-xin GAO ◽  
Xiang-yang MU ◽  
Nan TANG ◽  
Hong-liang YAN

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