Application of Genetic Algorithms for a Tyre Production Scheduling Information System

This paper, first, discusses a optimization scheduling problem which was considered as the manufacturing execution system was designed in a enterprise of manufacturing tyres. And then this problem is reduced to a scheduling problem to minimize setup times with batch setup time depending on sequence. A method for solving tyre production scheduling problem using an effective adaptive hybrid genetic algorithm is proposed. We advance a novel operator (looping & cutting operator) to improve the mountain climbing ability of the genetic algorithm, and put forward adaptive probabilities of crossover and mutation based on information entropy. Computational results show that the proposed adaptive hybrid genetic algorithm is effective and robust.