[1G1-GS-10] AI application

[1G1-GS-10-03] Two-Phase Optimization for Shift Scheduling in Individualized Teaching

〇Yosuke Suzuki¹, Kazunori Mizuno¹, Takaaki Toya² (1. Takushoku University, 2. Takushoku University)

Keywords:Genetic Algorithm, Constraint Satisfaction Problem, scheduling, Optimization, Simulated Annealing

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.