Friday 29th of March 2024
 

A Genetic Algorithm Approach for Solving a Flexible Job ShopScheduling Problem


Sayedmohammadreza Vaghefinezhad and Kuan Yew Wong

Flexible job shop scheduling has been noticed as an effective manufacturing system to cope with rapid development in todays competitive environment. Flexible job shop scheduling problem (FJSSP) is known as a NP-hard in the field of the optimization problem. Assuming the dynamic state of the real world, make these problems more and more complicated. Most studies in the field of FJSSP have only focused on minimizing the total makespan. In this paper, a mathematical model for FJSSP has been developed. The objective function is maximizing the total profit while meeting some constraints. Considering time-varying raw material and selling price and dissimilar demand for each period, are attempts that have been done to decrease gaps between reality and the model. A manufacturer that produces various parts of gas valves has been used as a case study. The scheduling problem for multi part, multi period, and multi operation with parallel machines has been solved by genetic algorithm (GA). The best obtained answer determines the economic amount of production by different machines that belong to predefined operations for each part to satisfy customer demand in each period.

Keywords: Flexible Job-Shop Scheduling, Optimization, Flexible Manufacturing System, Integer Programming, Genetic Algorithm

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ABOUT THE AUTHORS

Sayedmohammadreza Vaghefinezhad
Sayedmohammadreza Vaghefinezhad is a fulltime research student of Universiti Teknologi Malaysia (UTM) enrolled in the Doctor of Philosophy (Mechanical Engineering) program. He received Master of Engineering degree (Industrial Engineering) from UTM. He graduated in B.S course in the field of Industrial Engineering (Industrial Production) at Sharif University of Technology. His current research interests include operations research, simulation of operations, production and operations management, modeling and analysis of operation systems, evolutionary algorithms, and computer programming languages.

Kuan Yew Wong
Kuan Yew Wong received PhD degree from University of Birmingham in Manufacturing and Mechanical Engineering. He is a lecturer in Universiti Teknologi Malaysia (UTM). His main research interests include operations research, simulation of operations, engineering management, production and operations management, engineering and technology management, modeling and analysis of operation systems, computer-aided engineering drawing, information and knowledge management, facilities design, engineering mechanics–statics, engineering mechanics – dynamics.


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