A location-inventory-routing model for green supply chains with low-carbon emissions under uncertainty

The location-inventory-routing modeling is an integrated and comprehensive approach to the interconnected location planning, inventory management, and vehicle routing problems in supply chain management. Supplier selection and order allocation are critical operational and strategic decisions in gree...

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Bibliographic Details
Published in:Environmental science and pollution research international 2021-09, Vol.28 (36), p.50636-50648
Main Authors: Tavana, Madjid, Tohidi, Hamid, Alimohammadi, Milad, Lesansalmasi, Reza
Format: Article
Language:English
Subjects:
Algorithms
Aquatic Pollution
Atmospheric Protection/Air Quality Control/Air Pollution
Carbon
Component and supplier management
Earth and Environmental Science
Ecotoxicology
Emissions
Environment
Environmental Chemistry
Environmental Health
Environmental management
Environmental science
Integer programming
inventories
Inventory
Inventory management
Linear programming
Mixed integer
Multiple objective analysis
Research Article
Route planning
Solution space
Suppliers
supply chain
Supply chain management
Supply chain sustainability
Supply chains
Uncertainty
Vehicle routing
Waste Water Technology
Water Management
Water Pollution Control
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Summary:The location-inventory-routing modeling is an integrated and comprehensive approach to the interconnected location planning, inventory management, and vehicle routing problems in supply chain management. Supplier selection and order allocation are critical operational and strategic decisions in green supply chains. Green supply chain management is an environmental approach to sourcing and production that considers sustainability in every supply chain stage. In this study, a novel bi-objective mixed-integer linear programming model is formulated to solve the location-inventory-routing problems in green supply chains with low-carbon emissions under uncertainty. The proposed model is used for supplier selection and order allocation by considering the location priorities, heterogeneous vehicle routing, storage needs, uncertain demand, and backorder shortage. The formulated bi-objective model is solved with a weighted fuzzy multi-objective solution approach coupled with a novel intelligent simulation algorithm to ensure the feasibility of the solution space. We generate and solve different-sized problems to demonstrate the applicability and efficacy of the proposed model.
ISSN:0944-1344
1614-7499
DOI:10.1007/s11356-021-13815-8