A genetic algorithm with switch-device encoding for optimal partition of switched industrial Ethernet networks

This paper presents a novel genetic algorithm to solve the industrial Ethernet network partition problem (IENPP). A new switch-device encoding is presented for the problem, and incorporated into the genetic algorithm. This encoding has several advantages against the traditional representation used in previous approaches, which will be detailed in the paper. Also, several new genetic operators included in the genetic algorithm are described in the paper. Simulations in different network partition instances have shown the good performance of our approach: it obtains better results than a previous genetic algorithm due to the incorporation of the new representation and novel operators. Also the computational time of the proposed algorithm is better than that of the existing genetic algorithm for this problem.