Abstract: Due to the characteristics of long time-consuming, energy consumption and high concentration in rubber tire vulcanization process, which is the tire production process bottlenecks process, a discrete distribution estimation algorithm (EDA) was proposed to solve the problem of vulcanization shop scheduling optimization with minimum maximum completion time as the optimization target. The algorithm was tested by different examples, and it was compared with the genetic algorithm and the harmony search algorithm. The experimental results show that the EDA algorithm is superior to the genetic algorithm and the harmony search algorithm in the quality of the solution and convergence speed, and it verifies the effectiveness and feasibility of the algorithm in solving the vulcanization shop scheduling problem.

Key words: estimation of distribution algorithm, probabilistic model, vulcanization workshop scheduling, minimum completion time