改进万有引力算法在流水作业排序中的应用

The application of improved gravitation algorithm in flow sequencing

针对万有引力搜索算法在处理一些优化问题时比较容易出现早熟和搜索精度不高的缺点,通过引入变异思想和模拟退火思想,提出一种改进的万有引力搜索算法,并用此算法对以加权总误工最小为目标的流水作业排序优化问题进行分析,结果表明:改进后的万有引力算法明显优于传统万有引力算法.

Aiming at the shortcomings of universal gravitation search algorithm(GSA)in dealing with some optimization problems,such as precocity and low search accuracy,an improved universal gravitation search algorithm was proposed by introducing mutation and simulated annealing.Flow sequencing is a common combinatorial optimization problem in production operations.Different sequencing results in different maximum flow times and different products exceeding the deadline.In order to reduce the production time and the loss caused by missed work,the optimization problem of production sequencing is analyzed with the objective of minimizing the weighted total work delay.The results show that the improved gravitation algorithm is better than the traditional one.