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A Coevolutionary Genetic Based Scheduling Algorithm for stochastic flexible scheduling problem

机译：一种用于随机柔性调度问题的共耦合基于遗传调度算法

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摘要

Because traditional Genetic Algorithm has many limitations on solutions for the combined optimization problems, a Coevolutionary Genetic Based Scheduling Algorithm (CGBSA) is proposed for solving the stochastic flexible scheduling problem. In CGBSA, the number of sub-population is divided by the number of working procedure. The interaction of all sub-populations is reflected by means of the definition of fitness function. Based on stochastic programming theory and stochastic simulation, a model is presented object to minimize the maximum completion time, in which the processing time is uncertainty. Compared with GA, the simulation results validate the efficiency of the proposed stochastic schedule model and algorithm.
机译：由于传统的遗传算法对组合优化问题的解决方案具有许多限制，所以提出了一种基于共同遗传的调度算法（CGBSA）来解决随机柔性调度问题。在CGBSA中，子群的数量除以工作程序的数量。所有子群的相互作用是通过对健身功能的定义来反映的。基于随机编程理论和随机仿真，提出了一种模型，以最小化处理时间是不确定性的最大完成时间。与GA相比，仿真结果验证了所提出的随机调度模型和算法的效率。

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