论文部分内容阅读
提出了一种基于动态双子群的离散果蝇优化算法,求解以最大完工时间和机床空闲时间的最小化为目标的无等待流水线调度问题。与传统的果蝇算法不同,该算法采用基于工序的编码方式,并用改进的NEH方法进行初始化,提高初始解的质量;根据算法在进化过程中个体的进化水平,动态地将整个群体划分为先进子群和后进子群,简单但有效地插入方法在先进个体邻域内进化精细搜索,贪婪迭代进化机制用于优化后进个体,以此平衡算法的全局开发能力和局部搜索能力;为了提高算法效率,快速算法用于计算函数目标值和判断更新非支配解。仿真试验表明了所提果蝇算法的有效性和高效性。
This paper presents a discrete fruit fly optimization algorithm based on dynamic bi-subgroups and solves the problem of waiting queue without aiming at minimizing the maximum completion time and machine idle time. Different from the traditional Drosophila algorithm, this algorithm uses process-based coding and initializes with improved NEH method to improve the quality of the initial solution. According to the evolutionary level of the algorithm, the whole group is dynamically divided into advanced Subgroups and subgroups of subgroups. The method of simple but effective interpolation is used to refine the search in the neighborhoods of advanced individuals. The greedy iterative evolutionary mechanism is used to optimize the individuals and thus balance the global development ability and the local search ability. In order to improve the efficiency of the algorithm, The fast algorithm is used to calculate the target value of the function and to determine the update of the non-dominated solution. Simulation experiments show the efficiency and efficiency of the proposed fruit fly algorithm.