Technical gazette, Vol. 29 No. 5, 2022.
Original scientific paper
https://doi.org/10.17559/TV-20211022164333
Multi-Objective Flexible Job Shop Scheduling Using Genetic Algorithms
Attia Boudjemline
; Industrial Engineering Department, College of Engineering University of Ha'il, Saudi Arabia
Imran Ali Chaudhry
orcid.org/0000-0001-6726-0753
; Industrial Engineering Department, College of Engineering University of Ha'il, Saudi Arabia
Amer Farhan Rafique
; King Abdulaziz University, Jeddah, Saudi Arabia
Isam A-Q Elbadawi
; Industrial Engineering Department, College of Engineering, University of Ha'il, Saudi Arabia
Mohamed Aichouni
; Industrial Engineering Department, College of Engineering, University of Ha'il, Saudi Arabia
Mohamed Boujelbene
; Industrial Engineering Department, College of Engineering, University of Ha'il, Saudi Arabia
Abstract
Flexible Job Shop Scheduling is an important problem in the fields of combinatorial optimization and production management. This research addresses multi-objective flexible job shop scheduling problem with the objective of simultaneous minimization of: (1) makespan, (2) workload of the most loaded machine, and (3) total workload. A general-purpose, domain independent genetic algorithm implemented in a spreadsheet environment is proposed for the flexible job shop. Spreadsheet functions are used to develop the shop model. Performance of the proposed algorithm is compared with heuristic algorithms already reported in the literature. Simulation experiments demonstrated that the proposed methodology can achieve solutions that are comparable to previous approaches in terms of solution quality and computational time. Flexible job shop models presented herein are easily customizable to cater for different objective functions without changing the basic genetic algorithm routine or the spreadsheet model. Experimental analysis demonstrates the robustness, simplicity, and general-purpose nature of the proposed approach.
Keywords
flexible job shop scheduling; genetic algorithms; makespan; multi-objective; scheduling; spreadsheet
Hrčak ID:
281687
URI
Publication date:
15.10.2022.
Visits: 1.795 *