混合量子粒子群优化算法在高职院校排课管理系统中的应用  

Application of Hybrid Quantum Particle Swarm Optimization Algorithm in the Course Schedule Management System of Higher Vocational Colleges

作　　者：高建兴 GAO Jianxing(Gansu Vocational College of Architecture,Lanzhou Gansu 730050,China)

机构地区：[1]甘肃建筑职业技术学院,甘肃兰州730050

出　　处：《信息与电脑》2021年第17期47-49,共3页Information & Computer

摘　　要：高职院校排课管理是否合理直接影响了高等职业教育的质量,为了进一步提高教育质量和管理水平,笔者将混合量子粒子群优化算法作为研究工具,开展针对高职院校排课管理系统的优化研究。首先,根据粒子群优化算法相关理论,完成系统的总体设计和数据库设计;其次,从课表安排管理模块、课程设置模块、自动排课模块、课表查询模块、课表打印模块以及系统维护模块多个方面入手,完成对系统核心功能模块的设计;最后,对分别应用几种优化算法的系统运行性能进行测试,选出最优算法系统。测试结果表明,在混合量子粒子群优化算法的应用背景下,高职院校排课管理系统运行正常、稳定且性能最优,各个功能模块可实现设计相关要求,符合实际应用需求。Whether the scheduling management of higher vocational colleges is reasonable has a direct impact on the quality of higher vocational education. In order to further improve the quality of education and management level, this paper uses hybrid quantum particle swarm optimization algorithm as a research tool to develop a management system for higher vocational colleges optimization research. First, complete the overall design and database design of the system according to the theory of particle swarm optimization algorithm;secondly, from the timetable management module, the course setting module, the automatic lesson scheduling module, the timetable query module, the timetable printing module, and the system maintenance module. Start to complete the design of the core functional modules of the system;finally, test the performance of the system using several optimization algorithms, and select the optimal algorithm system. The test results show that under the application background of the hybrid quantum particle swarm optimization algorithm, the schedule management system of higher vocational colleges runs normally, stably, and has the best performance. Each functional module achieves design-related requirements and meets actual application requirements.

关 键 词：排课 粒子群优化算法 组合优化 

分 类 号：TP391.6[自动化与计算机技术—计算机应用技术] TP18[自动化与计算机技术—计算机科学与技术]