基于灰熵关联分析的流水车间多目标调度优化及算法实现

求解流水车间多目标调度优化问题及算法适应度值分配问题, 结合灰色关联度分析方法及信息熵理论提出灰熵关联度适应值分配策略, 利用灰关联系数结合熵值权重计算适应度值, 以灰熵关联度值引导启发式算法进化. 将该方法应用到差分算法及遗传算法中解决三目标流水车间调度问题. 实验表明: 灰熵关联度适应值分配策略能够解决该问题, 可以得到分布均匀的Pareto 前端; 同时, 基于此策略的差分算法得到的解好于遗传算法的解.

Flow shop multi-objective scheduling optimization research based on grey entropy relation analysis and the algorithm realization

In order to solve the flow shop multi-objective scheduling optimization problem and the algorithm fitness value assignment problem, the distribution strategy of the grey entropy relational adaptive value is proposed combined with grey correlation analysis method and the theory of the information entropy, and the fitness value is calculated combined with the grey correlation and entropy weight coefficient. The grey entropy correlation grade is used to guide the evolution of the heuristic algorithm. This method is introduced to the difference algorithm and the genetic algorithm to solve three objective flow shop scheduling problem. The experimental results show that grey entropy relational adaptive value allocation strategies can solve this problem effectively, and can get uniform distribution of the Pareto front. Meanwhile, the difference algorithm based on this strategy can abtain better solutions than the genetic algorithm.