Two-Phase Optimization for Shift Scheduling in Individualized Teaching

Abstract

A shift schedule is essential for managing the work of each employee. However, it is difficult to manually create a shift schedule while taking into account various constraints such as the days employees are available to work and the congestion in the store. In Individualized teaching addressed in our study also, it is necessary to take into account many constraints that include not only available workdays of instructors and subjects they can teach but also days and subjects students can take. In other words, scheduling for Individualized teaching is necessary to find both of a shift schedule for instructors and a subject timetable for students, being useful to develop a system to automatically create a proper schedule satisfying their constraints. In this paper, we propose a two phase optimization method that creates a shift schedule using genetic algorithms and a timetable for students using simulated annealing.