A Genetic Algorithm Approach for Solving a Flexible Job ShopScheduling Problem
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.
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.