Modelling of sustainable food grain supply chain distribution system : a bi-objective approach

Mogale, D.G. (Indian Institute of Technology Kharagpur, West Bengal, India) ; Cheikhrouhou, Naoufel (Haute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale) ; Tiwari, Manoj Kumar (Indian Institute of Technology Kharagpur, West Bengal, India)

Growing food demand, environmental degradation, post-harvest losses and the dearth of resources encourage the decision makers from developing nations to integrate the economic and environmental aspects in food supply chain network design. This paper aims to develop a bi-objective decision support model for sustainable food grain supply chain considering an entire network of procurement centres, central, state and district level warehouses, and fair price shops. The model seeks to minimise the cost and carbon dioxide emission simultaneously. The model covers several problem peculiarities such as multi-echelon, multi-period, multi-modal transportation, multiple sourcing and distribution, emission caused due to various motives, heterogeneous capacitated vehicles and limited availability, and capacitated warehouses. Multiple realistic problem instances are solved using the two Pareto based multi-objective algorithms. Sensitivity analysis results imply that the decision makers should establish a sufficient number of warehouses in each producing and consuming states by maintaining the suitable balance between the two objectives. Various policymakers like Food Corporation of India, logistics providers and state government agencies will be benefited from this research study.


Keywords:
Article Type:
scientifique
Faculty:
Economie et Services
School:
HEG - Genève
Institute:
CRAG - Centre de Recherche Appliquée en Gestion
Subject(s):
Economie/gestion
Date:
2019-09
Pagination:
24 p.
Published in:
International Journal of Production Research
Numeration (vol. no.):
To be published
DOI:
ISSN:
0020-7543
Appears in Collection:



 Record created 2019-09-27, last modified 2019-09-30

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