基于遗传算法的混合流水线车间调度多目标求解*

为了解决传统的多目标优化算法难以很好实现企业的实际决策需要问题，针对混合流水线车间调度（HFSP）的多目标优化调度问题，提出了一种新的多目标遗传算法。根据企业实际需求，采用分模块两层建模的思想，将多目标分为约束性目标和优化性目标。算法根据目标性质的不同分别进行不同的搜索。最后将新算法应用于HFSP多目标优化问题进行实例验证。结果表明，所提出的算法具有很好的可行性，与其他多目标优化方法相比,该算法具有明显的优越性、实用性和可操作性。

Solving multi-objective hybrid flow-shop scheduling problem based on genetic algorithm

In order to solve the problem that the traditional multi-objective optimization algorithm is difficult to realize the practical decision of the enterprise, brought a novel multi-objective genetic algorithm forward to solve the hybrid flow-shop scheduling problems. According to the demand of the enterprise, based on sub-module using two modeling ideas, objectives were fallen into two categories: constrained objective and optimized objective, and the different objective had the different searching process. Finally, it used the novel algorithm to solve the multi-objective hybrid flow-shop scheduling problem. The result shows that the novel algorithm has the good feasibility, and it also has an obvious advantage, the better practicability and maneuverability, compared with the traditional multi-objective optimization methods.