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本文将基于原始的遗传算法,采用创新的初始种群构建方法、优化的种群演化策略,结合与之相适应的编码,提出一种适用于处理多约束条件的高校排课方案。本排课办法中,针对遗传算法本身的缺点进行了大量优化,强化了初始种群,加快了排课结果推导速度,优化了近优解的评定方法。通过将变种的遗传算法应用于高校具体排课任务,测试并评定结果,验证了该方法相较传统的遗传算法的优越性。
Based on the original genetic algorithm, this paper proposes an innovative initial population construction method and an optimized population evolution strategy, combined with the corresponding coding, to propose a college course scheduling scheme suitable for dealing with multiple constraints. In this method, a great deal of optimization is made for the shortcomings of the genetic algorithm itself, which has strengthened the initial population, accelerated the derivation speed of the course arranging result and optimized the evaluation method of the near optimal solution. By applying the variant genetic algorithm to the specific course arranging tasks in colleges and universities, testing and evaluating the results, the superiority of this method to the traditional genetic algorithm is verified.