随着教育信息化的发展，高校课程管理逐渐向智能化方向迈进。在常州地区，由于多所高校对高效课程管理的需求日益增加，开发一款功能强大的排课表软件显得尤为重要。

本项目采用Python语言结合Django框架进行开发，通过构建数据库模型来存储教师、学生、教室等信息，并利用遗传算法优化排课逻辑。以下是关键代码片段：

        # models.py
        from django.db import models

        class Teacher(models.Model):
            name = models.CharField(max_length=50)
            subject = models.CharField(max_length=100)

        class Classroom(models.Model):
            number = models.IntegerField(unique=True)
            capacity = models.IntegerField()

        class Course(models.Model):
            title = models.CharField(max_length=100)
            teacher = models.ForeignKey(Teacher, on_delete=models.CASCADE)
            classroom = models.ForeignKey(Classroom, on_delete=models.CASCADE)
            start_time = models.TimeField()
            end_time = models.TimeField()
        

在算法层面，我们使用遗传算法（Genetic Algorithm）解决复杂的课程调度问题。以下为遗传算法的核心部分：

        # ga.py
        import random

        def create_population(pop_size, chromosome_length):
            return [[random.randint(0, 1) for _ in range(chromosome_length)] for _ in range(pop_size)]

        def fitness_function(individual):
            conflicts = 0
            for i in range(len(individual)):
                if individual[i] == 1:
                    conflicts += sum([1 for j in range(i+1, len(individual)) if individual[j] == 1])
            return -conflicts

        def evolve(population, fitness_func, mutation_rate):
            population.sort(key=lambda x: fitness_func(x), reverse=True)
            new_population = []
            for i in range(len(population)):
                parent1 = population[random.randint(0, len(population)-1)]
                parent2 = population[random.randint(0, len(population)-1)]
                child = crossover(parent1, parent2)
                child = mutate(child, mutation_rate)
                new_population.append(child)
            return new_population
        

此外，为了提升用户体验，前端界面采用了Vue.js框架，确保操作直观便捷。通过以上技术组合，系统能够快速生成合理的课程表，并支持实时调整。

总结而言，该排课表软件不仅满足了常州高校的实际需求，还展示了现代信息技术在教育领域的广泛应用前景。