在当今信息化时代，智慧校园的概念日益普及，旨在利用先进的信息技术提升教育管理效率和服务质量。排课系统作为智慧校园的重要组成部分之一，对于提高教学资源利用率、优化课程安排具有重要意义。本文将重点讨论一个针对南京地区开发的排课系统的设计与实现。

首先，我们从需求分析入手，明确了系统应具备的基本功能：支持多教师、多教室的复杂课程表安排；能够自动检测并避免时间冲突；同时考虑教师偏好和学生选课情况等因素。基于这些需求，我们采用了遗传算法作为核心排课策略，以期达到最优解。

下面是部分关键代码片段：

        import random

        class Course:
            def __init__(self, name, teacher, students):
                self.name = name
                self.teacher = teacher
                self.students = students

        def generate_initial_population(population_size, courses):
            population = []
            for _ in range(population_size):
                schedule = {}
                for course in courses:
                    time_slot = random.choice(list(range(10)))
                    if time_slot not in schedule.values():
                        schedule[course.name] = time_slot
                population.append(schedule)
            return population

        def fitness_function(schedule, courses):
            conflicts = 0
            for course in courses:
                if list(schedule.values()).count(schedule[course.name]) > 1:
                    conflicts += 1
            return -conflicts

        def genetic_algorithm(courses, population_size=100, generations=1000):
            population = generate_initial_population(population_size, courses)
            best_schedule = None
            best_fitness = float('-inf')
            for generation in range(generations):
                new_population = []
                for i in range(population_size):
                    parent1 = random.choice(population)
                    parent2 = random.choice(population)
                    child = crossover(parent1, parent2)
                    child = mutate(child)
                    fitness = fitness_function(child, courses)
                    if fitness > best_fitness:
                        best_fitness = fitness
                        best_schedule = child
                    new_population.append(child)
                population = new_population
            return best_schedule
        

上述代码展示了遗传算法的核心部分，包括初始化种群、适应度函数以及进化过程。通过不断迭代优化，最终得到满足条件的课程表安排方案。

总之，本研究提出的排课系统设计方案不仅解决了传统手工排课效率低下的问题，还通过引入先进的算法提高了课程安排的质量，为智慧校园建设提供了有力的技术支撑。