Consulting Scheduling of Vocational Planning in Colleges and Universities Based on Improved Genetic Algorithms

Abstract

In the work of promoting vocational planning education and consultation in colleges and universities, there are some problems, such as fewer teachers and more students, will make it difficult to complete the consultation for all students in a limited time. Focusing this problem, this paper makes a research on consulting scheduling of vocational planning in colleges and universities based on an improved genetic algorithms (IGA). Firstly, an improved genetic algorithm (IGA) is proposed in combination with the characteristics of the problem, which can realize the full coverage of the student consultation as soon as possible under the reasonable consideration of the workload and consultation time of the consultation teacher. The problem is coded by double-string method, different genetic operators are used for different characteristics of the string, and enhanced search operation is introduced to strengthen the optimal individual in the population. The results show that the IGA is more accurate and stable than the traditional genetic algorithm for promoting vocational planning education and consultation. The effectiveness of the improved strategy is verified by a simulation test. It is a feasible and reasonable scheduling algorithm for allocating consultation resources.