AN ELECTROMAGNETISM ALGORITHM OF NEURAL NETWORK ANALYSIS—AN APPLICATION TO TEXTILE RETAIL OPERATION
Peitsang Wu, Wen-Hung Yang, Nai-Chieh Wei · Journal of the Chinese Institute of Industrial Engineers · 2004
This paper applies a heuristic algorithm, called the “Electromagnetism Algorithm” (EM) [3], for neural network training. We develop a meta-model of the relationships between key inputs and performance measures of an apparel retail operations using neural network technology. This method simulates the electromagnetism theory of physics by considering each weight connection in a neural network as an electrical charge. Through the attraction and repulsion of the charges, weights move toward the optimality without being trapped into local optima like other algorithms such as genetic algorithm and gradient descent method. The computation results show that the EM algorithm not only converges much faster than those of genetic algorithms and back propagation algorithms in terms of CPU time but also saves more memories than those in genetic algorithms and back propagation algorithms.