An introduction of preference based stepping ahead firefly algorithm for the uncapacitated examination timetabling

Abstract

In recent times, there has been a growing attention to intelligent optimization algorithms centred on swarm principles such as the firefly algorithm (FA). It was proposed for the continuous domain that mimics the attraction of fireflies to flashing light and has been used in discrete domains via modification. A discrete domain that is a major challenge in most higher education institutes (HEI) is examination timetabling. This article presents a new methodology based on FA for uncapacitated examination timetabling problems (UETP) where the proposed method is an extension of earlier work by the authors on the continuous domain. UETP is considered in this article as it is a university examination timetabling problem, which is still an active research area and has not been solved by FA algorithm as per authors knowledge. The proposed method concentrates on solving the initial solution using discrete FA where it consolidates the reordering of examinations and slots through a heuristic ordering known as neighborhood search. Three neighborhoods are employed in this research, where one is used during the initialization phase while two are utilized during solution improvement phase. Later, through preference parameters, a novel stepping ahead mechanism is used, which employs neighborhood searches built on previous searches. The proposed method is tested with 12 UETP problems where the preference based stepping ahead FA creates comparative results to the best ones available in the literature for the Toronto exam timetabling dataset. The results obtained are proof of concept at the preliminary stage and require further experiments on other educational datasets such as the second international timetable competition benchmark sets. The newly introduced preference based stepping ahead mechanism takes advantage of the current best solution space where it exploits the solution space for better solutions. This paves the way for researchers to utilize the mechanism in other domains such as robotics, etc.

Opposition‐based ideal gas molecular movement algorithm with Cauchy mutation, velocity clamping, and mirror operator

“…The results are compared with the other well‐known optimization algorithms, including FA, PSO, ABC, GA, HS, and DE algorithms. The parameter settings in all experiments for each algorithm are shown in Table 11 (Mernik et al, 2006; Anguluri et al, 2011; Ramani & Balasubramanian, 2011; Li‐min, 2015; Patel & Savsani, 2015; Xueyan & Zheng, 2015; Nand et al, 2022).…”

“…Minimizing the weight of the beam has been defined as the purpose of the problem; the heights (or widths) of the different hollow blocks and the vertical displacement have also been considered the design variable and constraint of this problem, respectively. According to (Naruei & Keynia, 2021), the optimization problem is following:…”

“…OverallNote: Bold values denote the optimal/best solution found.T A B L E 7Overall Note: Bold values denote the optimal/best solution found. algorithm are shown in Table 11(Mernik et al, 2006;Anguluri et al, 2011;Ramani & Balasubramanian, 2011;Li-min, 2015;Patel & Savsani, 2015;Xueyan & Zheng, 2015;Nand et al, 2022).Tables 12-15 indicate all comparison results of mean, standard deviation, and best and worst values for benchmark functions. The lowest obtained values are assumed as the best results, which are marked in bold.…”

Preference-Based Stepping Ahead Firefly Algorithm for Solving Real-World Uncapacitated Examination Timetabling Problem

“…Researchers have explored various methods, including graph coloring techniques, to address the ETP [16], [17]. In recent years, evolutionary algorithms have emerged as a powerful alternative to traditional graph coloring techniques for solving the ETP, leveraging concepts from natural selection to optimize exam schedules [18]- [21]. An evolutionary algorithm that is simple in structure and has the ability to improve exploration and exploitation is the Firefly Algorithm (FA).…”

“…This research is an extension of [21], where a modified version of discrete FA, termed the 'Preference-Based Stepping Ahead Firefly Algorithm,' was introduced to the Uncapacitated Examination Timetabling Problem (UETP). It extends the application to a real-world problem together with encroachments to the proposed method using threshold acceptance.…”