Optimal allocation of purchasing orders to multiple suppliers

Globalization has given rise to an increasing number of businesses relying on outsourcing to fulfill their demands for non-critical products and services. Along with this trend comes the need to develop effective supply chain management strategies to ensure reliable sources of goods and services. In...

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Main Author: Chaw, Jason Yew Chuan.
Other Authors: Lee Siang Guan, Stephen
Format: Final Year Project
Language:English
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/10356/40262
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-402622023-03-04T18:42:36Z Optimal allocation of purchasing orders to multiple suppliers Chaw, Jason Yew Chuan. Lee Siang Guan, Stephen School of Mechanical and Aerospace Engineering A*STAR DRNTU::Engineering::Systems engineering Globalization has given rise to an increasing number of businesses relying on outsourcing to fulfill their demands for non-critical products and services. Along with this trend comes the need to develop effective supply chain management strategies to ensure reliable sources of goods and services. In the manufacturing sector, this translates into a need to identify suitable suppliers and determine optimal quantities to order from each supplier. This project addresses the issue of order allocation in single item, multiple supplier purchasing situations after suppliers have been pre-selected. Firstly, a cost model based on the Total Cost of Ownership concept is introduced to quantify the “real” cost of purchasing an item from a particular supplier. Secondly, a unique profile to characterize the performance of each supplier is generated using a Monte Carlo simulation. Utilizing this profile, Modern Portfolio Theory, an investment analysis tool used to minimize risk in investing, is adapted to analyze the scenario, and determine the optimal order size to be allocated to two or three suppliers by minimizing the standard deviation of the Purchase Cost. The use of Modern Portfolio Theory enables two stochastic variables, namely product quality and delivery lead time uncertainty, to be considered in the supplier allocation problem – a key feature many supplier allocation techniques currently lack. To take into account buyers’ varying risk appetites, a Risk Propensity Quotient is incorporated to help buyers decide on the best trade-off between minimizing Purchase Cost and minimizing risk. The proposed model is validated by testing it against two hypotheses developed after reviewing similar work, and found to behave in a manner which is consistent with these theories. The results indicate that Modern Portfolio Theory is a good candidate for order allocation provided the number of suppliers under consideration is small (two or three suppliers), and product quality and lead time reliability outweigh cost concerns. Bachelor of Engineering (Mechanical Engineering) 2010-06-14T04:14:44Z 2010-06-14T04:14:44Z 2010 2010 Final Year Project (FYP) http://hdl.handle.net/10356/40262 en Nanyang Technological University 50 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Systems engineering
spellingShingle DRNTU::Engineering::Systems engineering
Chaw, Jason Yew Chuan.
Optimal allocation of purchasing orders to multiple suppliers
description Globalization has given rise to an increasing number of businesses relying on outsourcing to fulfill their demands for non-critical products and services. Along with this trend comes the need to develop effective supply chain management strategies to ensure reliable sources of goods and services. In the manufacturing sector, this translates into a need to identify suitable suppliers and determine optimal quantities to order from each supplier. This project addresses the issue of order allocation in single item, multiple supplier purchasing situations after suppliers have been pre-selected. Firstly, a cost model based on the Total Cost of Ownership concept is introduced to quantify the “real” cost of purchasing an item from a particular supplier. Secondly, a unique profile to characterize the performance of each supplier is generated using a Monte Carlo simulation. Utilizing this profile, Modern Portfolio Theory, an investment analysis tool used to minimize risk in investing, is adapted to analyze the scenario, and determine the optimal order size to be allocated to two or three suppliers by minimizing the standard deviation of the Purchase Cost. The use of Modern Portfolio Theory enables two stochastic variables, namely product quality and delivery lead time uncertainty, to be considered in the supplier allocation problem – a key feature many supplier allocation techniques currently lack. To take into account buyers’ varying risk appetites, a Risk Propensity Quotient is incorporated to help buyers decide on the best trade-off between minimizing Purchase Cost and minimizing risk. The proposed model is validated by testing it against two hypotheses developed after reviewing similar work, and found to behave in a manner which is consistent with these theories. The results indicate that Modern Portfolio Theory is a good candidate for order allocation provided the number of suppliers under consideration is small (two or three suppliers), and product quality and lead time reliability outweigh cost concerns.
author2 Lee Siang Guan, Stephen
author_facet Lee Siang Guan, Stephen
Chaw, Jason Yew Chuan.
format Final Year Project
author Chaw, Jason Yew Chuan.
author_sort Chaw, Jason Yew Chuan.
title Optimal allocation of purchasing orders to multiple suppliers
title_short Optimal allocation of purchasing orders to multiple suppliers
title_full Optimal allocation of purchasing orders to multiple suppliers
title_fullStr Optimal allocation of purchasing orders to multiple suppliers
title_full_unstemmed Optimal allocation of purchasing orders to multiple suppliers
title_sort optimal allocation of purchasing orders to multiple suppliers
publishDate 2010
url http://hdl.handle.net/10356/40262
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