单台机器模糊加工时间排序问题的遗传算法

Genetic algorithm for scheduling problem of single machine with triangular fuzzy processing time

根据三角形模糊数的特性,在对总加工时间模糊度有约束的条件下,构造出NP-困难的1 fuzzy m in∑i=1Ci排序模型的遗传算法.并采用算例进行了仿真实验,验证算法的有效性.同时重点研究了设计的分段线性适应度函数的适用性.实例计算表明,通过调节适应度函数中的惩罚系数α和β,可以兼顾种群的多样性和促使搜索效率的提高.该算法的实际应用可行,且具有良好的收敛性和较高的搜索效率.

According to the property of triangular fuzzy number, a genetic algorithm and a scheduling model NP- hard of 1｜fuzzy｜min∑i=1^n Ci were constructed under the condition of total processing time with restricted span fuzzy extent. One computation test case was developed for simulation to verify the effectiveness of this algorithm. At the same time, the key issue of applicability of designed subsection-linearity fitness value function was studied. The example expounded that, the diversity of population and the searching efficiency can be improved by adjusting the penalty modulus in fitness value function, α and β. This algorithm can be potentially implemented in practical case, and has better astringency and searching efficiency.