Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/30170
Title: Coordinated scheduling of the transfer lots in an assembly-type supply chain: A genetic algorithm approach
Authors: Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.
0000-0002-4924-7587
0000-0002-6260-0162
İnkaya, Tülin
Akansel, Mehmet
AAH-2155-2021
ABE-6702-2020
24490728300
55288514900
Keywords: Computer science
Engineering
Assembly-type supply chain
Genetic algorithm
Lot streaming
Supply chain coordination
Management
Systems
Environment
Inventory
Delivery
Network
Model
Time
Algorithms
Chains
Genetic algorithms
Scheduling
Stream flow
Supply chains
Assembly
Coordinated scheduling
Genetic algorithm approach
Inventory costs
Lot streaming
Optimal transfers
Supply chain coordination
Supply chain performance
Work in process inventories
Issue Date: 20-Jan-2015
Publisher: Springer
Citation: İnkaya, T. ve Akansel, M. (2017). ''Coordinated scheduling of the transfer lots in an assembly-type supply chain: A genetic algorithm approach''. Journal of Intelligent Manufacturing, 28(4), 1005-1015.
Abstract: In this study, we consider coordinated scheduling of the transfer lots in an assembly-type supply chain. An assembly-type supply chain consists of at least two stages, where the upstream stages manufacture the components for several products to be assembled at the downstream stages. In order to enable faster flow of products through the supply chain and to decrease the work-in-process inventory, the concept of lot streaming is used as a means of supply chain coordination. We introduce a mathematical model, which finds the optimal transfer lot sizes in the supply chain. The objective is the minimization of the sum of weighted flow and inventory costs. We develop genetic algorithm (GA) based heuristics to solve the proposed model efficiently. The experimental results show that the proposed GA-based approaches provide acceptable results in reasonable amount of time. We also show that coordination with lot streaming provides improvements in the supply chain performance.
URI: https://doi.org/10.1007/s10845-015-1041-9
https://link.springer.com/article/10.1007/s10845-015-1041-9
1572-8145
http://hdl.handle.net/11452/30170
ISSN: 0956-5515
Appears in Collections:Scopus
Web of Science

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