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Grant: Discovery Grants Program - Individual

Toronto Metropolitan University

$22,000.00

Closed-loop supply chain configuration and optimization

FY 2022-23

Summary
In a forward supply chain, products are sent from suppliers to manufacturers and finally, to customers. In a reverse supply chain, some of the products are returned by customers. A closed-loop supply chain (CLSC) encompasses both forward and reverse supply chains. The goal of a CLSC (e.g. tire remanufacturing), is to gain economic and environmental values from both new and returned products. This program will pursue three primary areas of research in regards to CLSCs. First, this research is concerned with several sources of uncertainty within CLSCs, including the demand, return rate and quality of returned products. Our goal in this instance is to identify and analyze the different sources of uncertainty operating simultaneously in CLSC networks. Second, this research will consider how to minimize waste across CLSC networks, studying relevant environmental factors with a view to uncovering sustainable solutions. Third, this research will investigate the impact of Big Data on CLSC network configuration and optimization, given that large amounts of data are sometimes available within CLSC parameters. This research program will examine real case studies in Canada, CLSCs with a focus on four types of products: paper, tires, computers and hazardous materials. It will consider the typical CLSC networks of products, related recovery options (e.g. recycling), and federal and provincial policies in Canada. Moreover, it will propose mathematical models and develop appropriate solutions based on operations research techniques, e.g. robust optimization, multi-objective programming, and metaheuristic algorithms. Finally, it will provide relevant managerial insights and suggestions for practitioners focusing on Canadian industries.
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2017-04481
Name nom
Hassanzadeh Amin, Saman
Department département
Mechanical and Industrial Engineering - Mechanical and Industrial Engineering
Organization id
43
Institution établissement
Toronto Metropolitan University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2017
Award amount
22000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1509
Committee name en
Civil, Industrial and Systems Engineering
Committee name fr
Génie civil, industriel et des systèmes
Area of application code
520
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Production and operations management
Area of application fr
Production et gestion des opérations
Research subject code
1600
Research subject group en
Industrial engineering
Research subject group fr
Génie industriel
Research subject en
Industrial engineering
Research subject fr
Génie industriel
Installment
inst:6
Partie
1
Nb partie
7
Application title
Closed-loop supply chain configuration and optimization
Application summary
In a forward supply chain, products are sent from suppliers to manufacturers and finally, to customers. In a reverse supply chain, some of the products are returned by customers. A closed-loop supply chain (CLSC) encompasses both forward and reverse supply chains. The goal of a CLSC (e.g. tire remanufacturing), is to gain economic and environmental values from both new and returned products. This program will pursue three primary areas of research in regards to CLSCs. First, this research is concerned with several sources of uncertainty within CLSCs, including the demand, return rate and quality of returned products. Our goal in this instance is to identify and analyze the different sources of uncertainty operating simultaneously in CLSC networks. Second, this research will consider how to minimize waste across CLSC networks, studying relevant environmental factors with a view to uncovering sustainable solutions. Third, this research will investigate the impact of Big Data on CLSC network configuration and optimization, given that large amounts of data are sometimes available within CLSC parameters. This research program will examine real case studies in Canada, CLSCs with a focus on four types of products: paper, tires, computers and hazardous materials. It will consider the typical CLSC networks of products, related recovery options (e.g. recycling), and federal and provincial policies in Canada. Moreover, it will propose mathematical models and develop appropriate solutions based on operations research techniques, e.g. robust optimization, multi-objective programming, and metaheuristic algorithms. Finally, it will provide relevant managerial insights and suggestions for practitioners focusing on Canadian industries.