Grant: Alliance Grants
Cape Breton University
$24,748.00
Mathematical Modelling for Sustainable Supply Chain Network Design Under Uncertainty: Simulation-based Optimization Approach
FY 2023-24
Summary
Sustainable development has received growing attention in the past decade from policy makers, academics, and industry partners. Canadian developed Canola is a key player in the global supply chain, a crop that is now annually valued in Canada at $26.7 billion. The oil extracted from crushed canola and other oilseeds turns into environmentally friendly products with different applications in different sectors. Airesun's supply chain is expanding globally to make its various environmentally friendly, non-toxic, non-caustic, 100% biodegradable oil and lubricants accessible to different heavy industry sectors. Furthermore, this has the potential to create long-term societal and economic benefits for Canada, foreign countries involved, and people specifically women and youth hired to work in this global supply chain. However, operational delays, disruptions, and errors can occur in any echelon in a supply chain network. Furthermore, disruptions can occur due to geopolitics affecting procurement and logistics operations, pandemics causing near-full halt in product flow, industrial shifts, and operational failures and breakdowns. Besides, the transportation sector is one the largest source of greenhouse gas emissions, for example, accounting for more than 25% of total emissions in Canada in 2018. In this regard, discrete-event simulation modelling will be utilized to capture the probabilistic and imprecise nature of the parameters associated with decisions concerning product flow, transportation mode selection, and supply chain network cost while considering cost and carbon emissions objectives as well as uncertainties associated with lead time. In this regard, a multi-objective scenario-based optimization model will be developed to allow for incorporation of both minimum-cost and minimum-carbon-footprint solutions in the context of sustainable development. Each scenario will yield a different total cost, total revenue, and carbon footprint while satisfying customer demand at a given service level. The obtained solutions will be analyzed to inform the decision making processes involving procurement, transportation mode selection, and determining the number and capacity of facilities.
Program
Alliance Grants
Recipient
Location
Nova Scotia, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
576988-2022
Name nom
Ashtab, Sahand S
Department département
Business, Shannon School of
Organization id
84
Institution établissement
Cape Breton University
Province en
Nova Scotia
Province fr
Nouvelle-Écosse
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2022
Award amount
24748
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1206
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Engineering
Area of application fr
Génie
Research subject code
1600
Research subject group en
Industrial engineering
Research subject group fr
Industrial engineering
Research subject en
Génie industriel
Research subject fr
Génie industriel
Application title
Mathematical Modelling for Sustainable Supply Chain Network Design Under Uncertainty: Simulation-based Optimization Approach
Keyword
Environmental Sustainability; Multi-objective Optimization; Simulation Modelling; Social Sustainability; Supply Chain Network Design
Application summary
Sustainable development has received growing attention in the past decade from policy makers, academics, and industry partners. Canadian developed Canola is a key player in the global supply chain, a crop that is now annually valued in Canada at $26.7 billion. The oil extracted from crushed canola and other oilseeds turns into environmentally friendly products with different applications in different sectors. Airesun's supply chain is expanding globally to make its various environmentally friendly, non-toxic, non-caustic, 100% biodegradable oil and lubricants accessible to different heavy industry sectors. Furthermore, this has the potential to create long-term societal and economic benefits for Canada, foreign countries involved, and people specifically women and youth hired to work in this global supply chain. However, operational delays, disruptions, and errors can occur in any echelon in a supply chain network. Furthermore, disruptions can occur due to geopolitics affecting procurement and logistics operations, pandemics causing near-full halt in product flow, industrial shifts, and operational failures and breakdowns. Besides, the transportation sector is one the largest source of greenhouse gas emissions, for example, accounting for more than 25% of total emissions in Canada in 2018. In this regard, discrete-event simulation modelling will be utilized to capture the probabilistic and imprecise nature of the parameters associated with decisions concerning product flow, transportation mode selection, and supply chain network cost while considering cost and carbon emissions objectives as well as uncertainties associated with lead time. In this regard, a multi-objective scenario-based optimization model will be developed to allow for incorporation of both minimum-cost and minimum-carbon-footprint solutions in the context of sustainable development. Each scenario will yield a different total cost, total revenue, and carbon footprint while satisfying customer demand at a given service level. The obtained solutions will be analyzed to inform the decision making processes involving procurement, transportation mode selection, and determining the number and capacity of facilities.
