Young Hae Lee

Prof. Young Hae Lee

orcid

Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 September 2014 in Sustainability
Verified
Journal Article
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SMSonia Irshad Mari
Sonia Irshad Mari
YLYoung Hae Lee
Young Hae Lee
Muhammad Saad MemonMuhammad Saad Memon
Muhammad Saad Memon
Sustainable supply chain network design is a rich area for academic research that is still in its infancy and has potential to affect supply chain performance. Increasing regulations for carbon and waste management are forcing firms to consider their supply chains from ecological and social objectives, but in reality, however, facilities and the links connecting them are disrupted from time to time, due to poor weather, natural or manmade disasters or a combination of any other factors. Supply chain systems drop their sustainability objectives while coping with these unexpected disruptions. Hence, the new challenges for supply chain managers are to design an efficient and effective supply chain network that will be resilient enough to bounce back from any disruption and that also should have sufficient vigilance to offer same sustainability under a disruption state. This paper focuses on ecological sustainability, because an environmental focus in a supply chain system is more important and also links with other pillars of sustainability, as the products need to be produced, packed and transported in an ethical way, which should not harm social balance and the environment. Owing to importance of the considered issue, this paper attempts to introduce a network optimization model for a sustainable and resilient supply chain network by incorporating (1) sustainability via carbon emissions and embodied carbon footprints and (2) resilience by incorporating location-specific risks. The proposed goal programming (GP) model optimizes the total cost, while considering the resilience and sustainability of the supply chain network.

10 April 2002 in Computers & Industrial Engineering
Verified
Journal Article
Closed access
YLYoung Hae Lee
Young Hae Lee
MCMin Kwan Cho
Min Kwan Cho
SKSeo Jin Kim
Seo Jin Kim
YKYun Bae Kim
Yun Bae Kim

1 January 2016 in Mathematical Problems in Engineering
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Journal Article
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Muhammad Salman HabibMuhammad Salman Habib
Muhammad Salman Habib
YLYoung Hae Lee
Young Hae Lee
Muhammad Saad MemonMuhammad Saad Memon
Muhammad Saad Memon
In the past decade the humanitarian supply chain (HSC) has attracted the attention of researchers due to the increasing frequency of disasters. The uncertainty in time, location, and severity of disaster during predisaster phase and poor conditions of available infrastructure during postdisaster phase make HSC operations difficult to handle. In order to overcome the difficulties during these phases, we need to assure that HSC operations are designed in an efficient manner to minimize human and economic losses. In the recent times, several mathematical optimization techniques and algorithms have been developed to increase the efficiency of HSC operations. These techniques and algorithms developed for the field of HSC motivate the need of a systematic literature review. Owing to the importance of mathematical modelling techniques, this paper presents the review of the mathematical contributions made in the last decade in the field of HSC. A systematic literature review methodology is used for this paper due to its transparent procedure. There are two objectives of this study: the first one is to conduct an up-to-date survey of mathematical models developed in HSC area and the second one is to highlight the potential research areas which require attention of the researchers.

1 May 2013 in Computers & Industrial Engineering
Verified
Journal Article
Closed access
DCDong Won Cho
Dong Won Cho
YLYoung Hae Lee
Young Hae Lee

16 October 2016 in Sustainability
Verified
Journal Article
Open access
PDF file
SMSonia Irshad Mari
Sonia Irshad Mari
YLYoung Hae Lee
Young Hae Lee
Muhammad Saad MemonMuhammad Saad Memon
Muhammad Saad Memon
Researchers and practitioners are taking more interest in developing sustainable garment supply chains in recent times. On the other hand, the supply chain manager drops sustainability objectives while coping with unexpected natural and man-made disruption risks. Hence, supply chain managers are now trying to develop sustainable supply chains that are simultaneously resilient enough to cope with disruption risks. Owing to the importance of the considered issue, this study proposed a network optimization model for a sustainable and resilient supply chain network by considering sustainability via embodied carbon footprints and carbon emissions and resilience by considering resilience index. In this paper, initially, a possibilistic fuzzy multi-objective sustainable and resilient supply chain network model is developed for the garment industry considering economic, sustainable, and resilience objectives. Secondly, a possibilistic fuzzy linguistic weight-based interactive solution method is proposed. Finally, a numerical case example is presented to show the applicability of the proposed model and solution methodology.

1 April 2003 in Production Planning & Control
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Journal Article
Closed access
MLMu-Seong Lee
Mu-Seong Lee
YLYoung Hae Lee
Young Hae Lee
CJChan-Seok Jeong
Chan-Seok Jeong
Supplier selection process for supply chain management (SCM) and ISO 9001 quality management system environments is considered. Determining suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decisions is usually complex and unstructured. This paper proposes a high-quality-supplier selection (HQSS) model to deal with supplier selection problems in supply chain management. In selecting a supplier, quality management factors are considered first, and then price, delivery, etc. Quality management factors include a quality management audit, product testing, engineering work force, capability index, training time, etc., based on a five-interval scale. Next, the HQSS model determines the final solution by considering factors such as price, production lead-time, and delivery time.