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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时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。
In order to solve the problem of time-consuming, energy-intensive and high-concentration of rubber tire vulcanization process, a discrete estimation algorithm (Estimation of Distribution Algorithm, EDA) was proposed to solve the problem of vulcanization with minimizing the maximum completion time Workshop scheduling optimization problem. The performance of this algorithm is tested by different examples, and compared with genetic algorithm and harmony search algorithm. Experimental results show that EDA algorithm outperforms genetic algorithm and harmony search algorithm both in quality of optimization solution and convergence speed, and validates the effectiveness and feasibility of this algorithm in solving scheduling problems in curing shop.