An optimum closed loop supply chain network model in a stochastic product life cycle context

Nowadays, closed loop supply chain network (CLSCN) receives considerable attention due to the growing awareness of the environmental destruction and depletion of natural resources. The establishment of a CLSCN is considered as a strategic decision that requires a lot of effort and intensive capital...

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Main Author:	Madadi, Najmeh
Format:	Thesis
Language:	English
Published:	2016
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://eprints.utm.my/id/eprint/78819/1/NajmehMadadiPFKM2016.pdf
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spelling	my-utm-ep.788192018-09-17T04:20:48Z An optimum closed loop supply chain network model in a stochastic product life cycle context 2016-10 Madadi, Najmeh TJ Mechanical engineering and machinery Nowadays, closed loop supply chain network (CLSCN) receives considerable attention due to the growing awareness of the environmental destruction and depletion of natural resources. The establishment of a CLSCN is considered as a strategic decision that requires a lot of effort and intensive capital resources. Therefore, it is very crucial to make CLSCN design decisions taking into account multiple facets of uncertainties. Literature reviews to date reveals that uncertainties in product life cycle (PLC) or what has been called “product diffusion” have been vastly ignored. Particularly, the deterministic nature of the proposed diffusion models is a severe defect that can hinder the involvement of real-world uncertainties in design of a CLSCN. This study is an attempt to fill this gap by developing a costefficient CLSCN model for a product with dynamic and stochastic diffusion into the market that leads to an optimum design of the targeted CLSCN. Firstly, a geometric Brownian motion (GBM)-based diffusion forecast method was proposed and validated using a conventional approach namely, Holt’s method. Then, a two-stage stochastic programming mathematical model for optimum design of the targeted CLSCN was developed. The developed stochastic CLSCN model provides the optimum design of the targeted CLSCN utilizing the values predicted for the product diffusion through the PLC based on the proposed forecast method. The developed mathematical model addresses two types of decisions namely, “here and now” and “wait and see” decisions within the PLC. The “here and now” decisions were made in the first stage. The results show optimum values for decisions concerning configuration of the CLSCN as well as dynamic capacity allocation and expansion decisions through the PLC. However, the “wait and see” decisions are made in the second stage within the frame provided by the first-stage solutions. Here, the results portray optimum values for decisions concerning with the flow quantities between the CLSCN facilities, backorder and inventory levels, and recovery of returns through the PLC. In order to test the applicability of the developed CLSCN model, the mathematical model was coded by CPLEX software and solved for secondary data from the case study from previous case study in literature. Finally, a sensitivity analysis was performed to investigate the effect of diffusion uncertainty on the total cost of the CLSCN, its configuration, and production capacity allocations and expansions. The results of the sensitivity analysis revealed that, for the higher levels of diffusion uncertainty, the total cost imposed to the supply chain increases due to the increase in the allocated production capacity as well as the increase in the number of involved facilities. 2016-10 Thesis http://eprints.utm.my/id/eprint/78819/ http://eprints.utm.my/id/eprint/78819/1/NajmehMadadiPFKM2016.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:106256 phd doctoral Universiti Teknologi Malaysia, Faculty of Mechanical Engineering Faculty of Mechanical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Madadi, Najmeh An optimum closed loop supply chain network model in a stochastic product life cycle context
description	Nowadays, closed loop supply chain network (CLSCN) receives considerable attention due to the growing awareness of the environmental destruction and depletion of natural resources. The establishment of a CLSCN is considered as a strategic decision that requires a lot of effort and intensive capital resources. Therefore, it is very crucial to make CLSCN design decisions taking into account multiple facets of uncertainties. Literature reviews to date reveals that uncertainties in product life cycle (PLC) or what has been called “product diffusion” have been vastly ignored. Particularly, the deterministic nature of the proposed diffusion models is a severe defect that can hinder the involvement of real-world uncertainties in design of a CLSCN. This study is an attempt to fill this gap by developing a costefficient CLSCN model for a product with dynamic and stochastic diffusion into the market that leads to an optimum design of the targeted CLSCN. Firstly, a geometric Brownian motion (GBM)-based diffusion forecast method was proposed and validated using a conventional approach namely, Holt’s method. Then, a two-stage stochastic programming mathematical model for optimum design of the targeted CLSCN was developed. The developed stochastic CLSCN model provides the optimum design of the targeted CLSCN utilizing the values predicted for the product diffusion through the PLC based on the proposed forecast method. The developed mathematical model addresses two types of decisions namely, “here and now” and “wait and see” decisions within the PLC. The “here and now” decisions were made in the first stage. The results show optimum values for decisions concerning configuration of the CLSCN as well as dynamic capacity allocation and expansion decisions through the PLC. However, the “wait and see” decisions are made in the second stage within the frame provided by the first-stage solutions. Here, the results portray optimum values for decisions concerning with the flow quantities between the CLSCN facilities, backorder and inventory levels, and recovery of returns through the PLC. In order to test the applicability of the developed CLSCN model, the mathematical model was coded by CPLEX software and solved for secondary data from the case study from previous case study in literature. Finally, a sensitivity analysis was performed to investigate the effect of diffusion uncertainty on the total cost of the CLSCN, its configuration, and production capacity allocations and expansions. The results of the sensitivity analysis revealed that, for the higher levels of diffusion uncertainty, the total cost imposed to the supply chain increases due to the increase in the allocated production capacity as well as the increase in the number of involved facilities.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Madadi, Najmeh
author_facet	Madadi, Najmeh
author_sort	Madadi, Najmeh
title	An optimum closed loop supply chain network model in a stochastic product life cycle context
title_short	An optimum closed loop supply chain network model in a stochastic product life cycle context
title_full	An optimum closed loop supply chain network model in a stochastic product life cycle context
title_fullStr	An optimum closed loop supply chain network model in a stochastic product life cycle context
title_full_unstemmed	An optimum closed loop supply chain network model in a stochastic product life cycle context
title_sort	optimum closed loop supply chain network model in a stochastic product life cycle context
granting_institution	Universiti Teknologi Malaysia, Faculty of Mechanical Engineering
granting_department	Faculty of Mechanical Engineering
publishDate	2016
url	http://eprints.utm.my/id/eprint/78819/1/NajmehMadadiPFKM2016.pdf
_version_	1747818079027462144

An optimum closed loop supply chain network model in a stochastic product life cycle context

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