Abstract
Machinery industry enterprise as research background, this paper analyzed the feature of production scheduling for discrete manufacturing and proposed the collaborative multi-objective optimization problem. Based on the improved Taguchi loss function, nonlinear relationship of quality, delivery and cost was established. And the multi-objective collaborative optimization model of production scheduling was created as well as synthetically considering of discrete constraints. The effective solution was studied to solve the model integrating simulation modeling and genetic algorithm. Further, through the enterprise empirical study, the practicability and validity of the model and algorithm is verified. This study will improve the synergy degree among quality, delivery and cost three goals, and provide an effective theoretical method of production schedule for the discrete manufacturing.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
YANG Xiao-ying, SHI Guo-hong, WANG Xue. Combinatorial optimization of one-piece discrete production scheduling based on the lean logistics [J]. Industrial Engineering and Management, 2013, 18(3): 11-18. (Chinese)
Karl G Kempf, Pınar Keskinocak, Reha Uzsoy. Planning Production and Inventories in the Extended Enterprise: A State of the Art Handbook (Volume 1) [M]. Springer New York Dordrecht Heidelberg London, 2011.
LI Lin, HUO Jia-zhen. Multi-objective flexible Job-shop scheduling problem in steel tubes production [J]. Systems Engineering-Theory & Practice, 2009 (8): 117-126. (Chinese)
Susan K. Monkman, Douglas J. Morrice, Jonathan F. Bard. A production scheduling heuristic for an electronics manufacturer with sequence-dependent setup costs [J]. European Journal of Operational Research, 2008(187):1100–1114.
Jennifer Muñoz Blás. Development of a time-efficient heuristic method for production scheduling with resource constraints and changeover considerations [D]. INDUSTRIAL ENGINEERING UNIVERSITY OF PUERTO RICOMAYAGŰEZ CAMPUS December, 2007.
LI Chun, GE Mao-gen, ZHANG Ming-xin. Study on dynamic advanced planning and scheduling problem based on genetic and particle swarm optimization algorithm [J]. Journal of Hefei University of Technology (Natural Science), 2010, 33(1):5-9.
YI Jun, LI Taifu. Bacterial foraging optimization algorithm based on variable neighborhood for Job-shop scheduling problem [J]. Journal of Mechanical Engineering, 2012, 48(12):178-183. (Chinese)
Massimiliano Caramia, Stefano Giordani. A fast metaheuristic for scheduling independent tasks with multiple modes [J]. Computers & Industrial Engineering, 2010, 58:64–69.
AntonioLova, PilarTormos, Mariamar Cervantes, FedericoBarber. An efficient hybrid genetic algorithm for scheduling projects with resource constraints and multiple execution modes [J]. Int. J. Production Economics 2009(117):302–316.
LEE Yan-fei, JIANG Zhi-bin. Production scheduling optimization with time-variable multiple-objectives for semiconductor wafer fabrication system [J]. Journal of Shanghai Jiao Tong University, 2008(2):209-213. (Chinese)
SHI Guo-hong, CHEN Jing-xian, MA Han-wu, CHEN Ling-qing. Optimization scheduling research of multi-resource-constrained project based on mixed-intelligence algorithm [J]. Journal of Engineering Design, 2008(4). (Chinese)
Lin Wei. Multi-objective constraint environment of production planning and scheduling method [D]. Donghua university master’s degree thesis, 2008. (Chinese)
Zheng Boke, Xiaoying YANG. Optimization method of transfer batch adaptive job scheduling [J]. Journal of Henan University of Science and Technology: Natural Science, 2012, 33(2):17-21.
PAN Er-shun, LI Qing-guo. Improvement of Taguchi’s loss function and its application in optimal economy production quantity [J]. Journal of Shanghai Jiaotong University, 2005, 39(7): 1120-1122.(Chinese)
LI Jia-xiang, HAN Zhi-jun. Research on process control for multi-product and small-batch production based on Taguchi method [J]. Industrial Engineering and Management, 2009, 13(1): 31-35. (Chinese)
Acknowledgment
The authors gratefully acknowledge the support of the Henan Science and Technology Research Program, China (No. 102102210487) and Luoyang of Henan province Science and Technology Program, China (No. 1101027A, No. 20130703).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Atlantis Press and the authors
About this paper
Cite this paper
YANG, Xy., WANG, X., SUN, Hy. (2015). Multi-objective Collaborative Optimization of Production Scheduling for Discrete Manufacturing. In: Qi, E., Shen, J., Dou, R. (eds) Proceedings of the 21st International Conference on Industrial Engineering and Engineering Management 2014. Proceedings of the International Conference on Industrial Engineering and Engineering Management. Atlantis Press, Paris. https://doi.org/10.2991/978-94-6239-102-4_20
Download citation
DOI: https://doi.org/10.2991/978-94-6239-102-4_20
Published:
Publisher Name: Atlantis Press, Paris
Print ISBN: 978-94-6239-101-7
Online ISBN: 978-94-6239-102-4
eBook Packages: EngineeringEngineering (R0)