为解决橡胶轮胎硫化过程耗时长,能源消耗大,集中度较高的问题,提出了一种离散的分布估计算法(Estimation of Distribution Algorithm,EDA)来求解以最小化最大完工对间为优化目标的硫化车间调度优化问题.通过不同的算例来测试该算法的性能,并与遗传算法和和声搜索算法进行实验比较.实验结果表明,EDA算法在优化解的质量和收敛速度方面都要优于遗传算法和和声搜索算法,验证了该算法在求解硫化车间调度优化问题中的有效性和可行性.“,”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.