Using Genetic Algorithm Optimization for University Buildings Timetable Scheduling Based on Energy Efficiency: A Case Study of the Electrical Engineering Department, Assiut University

Abstract

Higher education administrators must actively develop their management strategies to lower building energy usage, as it is challenging to get students to adopt energy-saving behaviors due to their limited responsibilities. The increasing number of students, the variety of teaching processes, the lack of adequate educational facilities in some areas, limited availability of classrooms, and the scheduling preferences of lecturers and students are essential factors that affect schedule management. Programming for preparing academic timetables has become particularly difficult in recent years. The goal of this paper is to use the academic timetable as an effective tool to improve electrical energy consumption and to align students’ activities during their time in university buildings with energy efficiency. The goals of an optimum timetable can be achieved through three directions: human preferences, time slots, and space characteristics. This work uses a genetic algorithm to generate an optimum university schedule that considers building energy efficiency. The suggested technique simulates the schedule of a university teaching building in the Electrical Engineering Department at Assiut University, Assiut, Egypt, for the academic year 2023/2024. The optimized timetable shows a reduction in energy consumption of teaching spaces by approximately 20.6%. Moreover, it helps improve student and teacher activities during working hours through the design and operational management of teaching spaces