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针对飞机总装移动装配线的资源水平问题,以最小化资源成本为目标,提出并建立了具有空间约束的资源水平问题的数学模型。针对问题特点,提出了非关键任务调度优先级规则,并以遗传算法为框架,优化非关键任务调度优先级。在解码中,提出利用区间细分的方式来确定非关键任务位置,以提高计算效率,提出并设计了当前任务调度对全局资源水平影响的评估公式,极大提高了未调度任务在后续调度过程中选择更佳调度位置的几率。针对空间约束,构建了包含当前关键任务的局部调整方法。最后通过数据实验验证了算法的有效性和优越性。
In order to minimize the resource cost, aiming at the resource level of assembly line of aircraft assembly, a mathematic model of resource constrained resource level was proposed and established. According to the characteristics of the problem, the priority rules of non-mission-critical tasks are proposed. The priority of non-mission-critical tasks is optimized by using genetic algorithm as a framework. In the decoding, the method of interval subdivision is proposed to determine the position of non-critical tasks to improve the computational efficiency. The evaluation formula of the impact of the current task scheduling on the global resource level is proposed and designed, which greatly improves the unscheduled tasks in the subsequent scheduling process In the choice of a better chance of scheduling position. For the space constraints, a local adjustment method that contains the current key tasks is constructed. Finally, the data experiments show that the algorithm is effective and superior.