Optimization of multi-echelon supply chain kanban model using genetic algorithm

A supply chain system (SCS) consists of organizations or companies that utilizes approaches to have an effective relation between suppliers, manufacturers, warehouses, distribution centers, retailers and finally, the customers. Kanban system is an efficient and easy system to be implemented. In a ka...

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Main Author:	Sabaghi, Mahdi
Format:	Thesis
Language:	English
Published:	2011
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/26891/1/MahdiSabaghiMFKM2011.pdf
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spelling	my-utm-ep.268912018-05-27T06:36:31Z Optimization of multi-echelon supply chain kanban model using genetic algorithm 2011 Sabaghi, Mahdi TK Electrical engineering. Electronics Nuclear engineering A supply chain system (SCS) consists of organizations or companies that utilizes approaches to have an effective relation between suppliers, manufacturers, warehouses, distribution centers, retailers and finally, the customers. Kanban system is an efficient and easy system to be implemented. In a kanban system each plant sends signals to the following plant for needed parts. The kanban withdraws parts instead of pushing parts from one station to another station. The workstations are located along the production lines and only produce or deliver desired components when they receive a card. The number ofkanbans can significantly influence the load balance between processes and the amount of orders suppliers need to obtain from subcontractors. Large kanban size results in large amount of WIP inventory at each workstation. On the other side, although reducing kanban size causes a decrease in WIP inventory it leads to transportation increases as well as reduction in the system throughput rate. In this study a multi-echelon supply chain system controlled by kanban system, is considered. Decision making is based on determination of the number of kanbans as well as economic-quantity order of products. Since the adopted model used in this study is mixed integer non-linear programming (MINLP) type and solving it by exact algorithm such as branch and bound (B&B) takes a lot of time, a heuristic method via Genetic algorithm (GA) is presented. Some problems are solved by our proposed GA to illustrate the performance ofthe method. 2011 Thesis http://eprints.utm.my/id/eprint/26891/ http://eprints.utm.my/id/eprint/26891/1/MahdiSabaghiMFKM2011.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:78070?queryType=vitalDismax&query=+Optimization+of+multi-echelon+supply+chain+kanban+model+using+genetic+algorithm+&public=true masters Universiti Teknologi Malaysia, Faculty of Mechanical Engineering Faculty of Mechanical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Sabaghi, Mahdi Optimization of multi-echelon supply chain kanban model using genetic algorithm
description	A supply chain system (SCS) consists of organizations or companies that utilizes approaches to have an effective relation between suppliers, manufacturers, warehouses, distribution centers, retailers and finally, the customers. Kanban system is an efficient and easy system to be implemented. In a kanban system each plant sends signals to the following plant for needed parts. The kanban withdraws parts instead of pushing parts from one station to another station. The workstations are located along the production lines and only produce or deliver desired components when they receive a card. The number ofkanbans can significantly influence the load balance between processes and the amount of orders suppliers need to obtain from subcontractors. Large kanban size results in large amount of WIP inventory at each workstation. On the other side, although reducing kanban size causes a decrease in WIP inventory it leads to transportation increases as well as reduction in the system throughput rate. In this study a multi-echelon supply chain system controlled by kanban system, is considered. Decision making is based on determination of the number of kanbans as well as economic-quantity order of products. Since the adopted model used in this study is mixed integer non-linear programming (MINLP) type and solving it by exact algorithm such as branch and bound (B&B) takes a lot of time, a heuristic method via Genetic algorithm (GA) is presented. Some problems are solved by our proposed GA to illustrate the performance ofthe method.
format	Thesis
qualification_level	Master's degree
author	Sabaghi, Mahdi
author_facet	Sabaghi, Mahdi
author_sort	Sabaghi, Mahdi
title	Optimization of multi-echelon supply chain kanban model using genetic algorithm
title_short	Optimization of multi-echelon supply chain kanban model using genetic algorithm
title_full	Optimization of multi-echelon supply chain kanban model using genetic algorithm
title_fullStr	Optimization of multi-echelon supply chain kanban model using genetic algorithm
title_full_unstemmed	Optimization of multi-echelon supply chain kanban model using genetic algorithm
title_sort	optimization of multi-echelon supply chain kanban model using genetic algorithm
granting_institution	Universiti Teknologi Malaysia, Faculty of Mechanical Engineering
granting_department	Faculty of Mechanical Engineering
publishDate	2011
url	http://eprints.utm.my/id/eprint/26891/1/MahdiSabaghiMFKM2011.pdf
_version_	1747815535977955328

Optimization of multi-echelon supply chain kanban model using genetic algorithm

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