Multiobjective Order Assignment Optimization in a Global Multiple-Factory Environment
Joint Authors
Hung, Pei-Hsuan
Chen, Rong-Chang
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-01
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
In response to radically increasing competition, many manufacturers who produce time-sensitive products have expanded their production plants to worldwide sites.
Given this environment, how to aggregate customer orders from around the globe and assign them quickly to the most appropriate plants is currently a crucial issue.
This study proposes an effective method to solve the order assignment problem of companies with multiple plants distributed worldwide.
A multiobjective genetic algorithm (MOGA) is used to find solutions.
To validate the effectiveness of the proposed approach, this study employs some real data, provided by a famous garment company in Taiwan, as a base to perform some experiments.
In addition, the influences of orders with a wide range of quantities demanded are discussed.
The results show that feasible solutions can be obtained effectively and efficiently.
Moreover, if managers aim at lower total costs, they can divide a big customer order into more small manufacturing ones.
American Psychological Association (APA)
Chen, Rong-Chang& Hung, Pei-Hsuan. 2014. Multiobjective Order Assignment Optimization in a Global Multiple-Factory Environment. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-489381
Modern Language Association (MLA)
Chen, Rong-Chang& Hung, Pei-Hsuan. Multiobjective Order Assignment Optimization in a Global Multiple-Factory Environment. Mathematical Problems in Engineering No. 2014 (2014), pp.1-14.
https://search.emarefa.net/detail/BIM-489381
American Medical Association (AMA)
Chen, Rong-Chang& Hung, Pei-Hsuan. Multiobjective Order Assignment Optimization in a Global Multiple-Factory Environment. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-489381
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-489381