Abstract: In order to verify the genetic algorithm is better than heuristic rules in solving the surely flow shop scheduling problem, this paper analyzes the characteristics of the surely flow shop scheduling problem, and applies the new algorithm to solve the problem. In order to improve the search efficiency and avoid falling into local optimal solution, this paper proposes a new method of the initial population and successfully applies the method to solve the surely flow shop scheduling problem. The simulation experiment result proves the practicality, reliability, and super application value of the improved genetic algorithm.

Key words: workshop scheduling, genetic algorithm, surely flow-shop scheduling

摘要： 为了验证遗传算法在解决确定型流水车间调度问题比其他启发式算法优越，分析了确定型流水车间调度的特点，并运用一种新的遗传算法求解该问题。为了提高效率，避免陷入局部最优，提出了一种合理的种群初始化方法，并成功地运用于求解确定型流水车间调度问题。实验结果证明了改进的遗传算法的实用性和可靠性，并具有较好的应用价值。

关键词: 车间调度, 遗传算法, 确定型流水车间调度