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。
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