Multiple Teacher Transfer Optimization using Genetic Algorithms Case Study on Kindergarten Teacher Transfer

Abstract

This paper proposes an approach using Genetic Algorithm (GA) which has been proved an optimal searching approach for global solution to solve the Multiple Teacher Transfer problem. The current Multiple Teacher Transfer Operation (MTO) in Taiwan follows a matching procedure that he/she of the highest scores initiates operations of 2-sided, 3-sided, 4- sided and 5-sided Transfer between/among schools. The solution space is N! (N M)! , where N is the number of people in MTO, M is the number of transfer sides. Since MTO is a NP-Hard problem when M and N getting large it is difficult to solve by traditional determinative approach or by mathematical inference. In this paper, we propose a GA-based method by using maneuvers of string encoding, one-point crossover, neighbor search mutation, repairing, local search and diversity maintenance. Furthermore, conducting GA parameter design in accordance with Taguchi Method, the proposed method has proved to be able to break through restrictions of solution space of current operation and to pursue optimal solution, the improvement of successful cases increase up to 45%, after conducting experiments on public kindergarten teachers who failed in Single Teacher Posting Operation (SPO) from 2007 to 2008 in Taiwan, in accordance with “Operation of Application for Inter-City/County Transfer for Teachers of Public Junior High Schools, Elementary Schools and Kindergartens in Taiwan Area” (AITTOS).