電力系統の負荷融通問題におけるホップフィールド形ニューラルネットワークの適用

抄録

This paper presents a new application method of Hopfield-type neural networks for combinatorial optimization problems under inequality constraints.
Since Hopfield showed that the neural network technique could solve combinatorial problems such as the Traveling Salesman Problem, many researchers have attemped to apply the neurals networks to various problems. However, the constraints of almost all of those problems are limited to equality constraints.
To deal with the inequality constraints, we developed a new method in which we introduce special neurons that converge to intermediate values between 0 and 1. This method is applied to the switch pattern planning problem of power distribution systems. The stability analysis and simulation results show that the method is quite promising.