Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

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

Mogale, D. G., Cheikhrouhou, Naoufel and Kumar Tiwari, Manoj 2019. Modelling of sustainable food grain supply chain distribution system: a bi-objective approach. International Journal of Production Research 10.1080/00207543.2019.1669840
Item availability restricted.

[img] PDF - Accepted Post-Print Version
Restricted to Repository staff only until 10 September 2020 due to copyright restrictions.

Download (1MB)


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.

Item Type: Article
Date Type: Publication
Status: In Press
Schools: Business (Including Economics)
Publisher: Taylor & Francis
ISSN: 0020-7543
Date of First Compliant Deposit: 21 February 2020
Last Modified: 10 Mar 2020 16:59

Citation Data

Cited 2 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics