德阳市高中排课系统的实现与优化

def schedule_courses(courses, teachers, rooms, time_slots):

import itertools

from random import shuffle

# 创建一个初始的课程表

course_table = {}

for t in teachers:

course_table[t] = {slot: None for slot in time_slots}

# 生成所有可能的课程分配组合

possible_assignments = list(itertools.product(courses, teachers, rooms, time_slots))

shuffle(possible_assignments)

# 尝试将课程分配到时间表中

for course, teacher, room, slot in possible_assignments:

if course_table[teacher][slot] is None:

course_table[teacher][slot] = (course, room)

return course_table

courses = ["数学", "物理", "化学", "生物"]

teachers = ["张老师", "李老师", "王老师", "赵老师"]

rooms = ["A教室", "B教室", "C教室"]

time_slots = ["上午第一节", "上午第二节", "下午第一节", "下午第二节"]

schedule = schedule_courses(courses, teachers, rooms, time_slots)

print(schedule)

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迎新管理软件

def genetic_algorithm(courses, teachers, rooms, time_slots, generations=1000, population_size=100):

# 这里是一个简化的遗传算法实现

pass

best_schedule = genetic_algorithm(courses, teachers, rooms, time_slots)

print(best_schedule)

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