Mohd Abdul Hadi, Osman and Mohd Fadzil Faisae, Ab Rashid and Muhammad Ammar, Nik Mu’tasim (2024) A whale optimization algorithm approach for flow shop scheduling to minimize makespan. Journal of Modern Manufacturing Systems and Technology (JMMST), 8 (2). pp. 12-32. ISSN 2636-9575. (Published)
|
Pdf
43980.pdf Available under License Creative Commons Attribution Non-commercial. Download (578kB) | Preview |
Abstract
Flow shop scheduling is crucial in manufacturing and production environments because it directly impacts output and overall production efficiency. It involves processing a set of jobs on multiple machines in a specific order. The objective is to determine the optimal job sequence that minimizes the makespan, which is the total time required to complete all jobs. This study proposes a computerized approach utilizing the Whale Optimization Algorithm (WOA) to solve the flow shop scheduling problem and minimize the makespan. The WOA is a recently developed meta-heuristic algorithm inspired by the bubble-net hunting strategy of humpback whales. The performance of the WOA is evaluated using five benchmark problems with varying numbers of jobs and machines, and the results are compared with those obtained from other algorithms reported in the literature, such as genetic algorithms and heuristic models. The findings demonstrate that the WOA can effectively solve the flow shop scheduling problem and provide improved makespan values, with an average efficiency of 7.33% compared to the other algorithms.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Flow shop scheduling; Scheduling optimization; Whale optimization algorithm; Metaheuristics |
Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TS Manufactures |
Faculty/Division: | Faculty of Mechanical and Automotive Engineering Technology Faculty of Manufacturing and Mechatronic Engineering Technology |
Depositing User: | Dr. Mohd Fadzil Faisae Ab. Rashid |
Date Deposited: | 02 Oct 2024 07:38 |
Last Modified: | 02 Oct 2024 07:38 |
URI: | http://umpir.ump.edu.my/id/eprint/42706 |
Download Statistic: | View Download Statistics |
Actions (login required)
View Item |