Title
An integrated AHP-DEA multi-objective optimization model for sustainable transportation in mining industry
Date Issued
01 December 2021
Access level
metadata only access
Resource Type
journal article
Author(s)
Gupta P.
Mehlawat M.K.
Aggarwal U.
University of Buckingham
Publisher(s)
Elsevier Ltd
Abstract
Due to increased attention to coal mining, the industrial transport in most countries including India necessitated search for sustainable transportation leading to environmental protection, maximum speed of delivery, minimum cost of transportation, and enhanced traffic safety. In this paper, we formulate an integrated multi-objective optimization model for an extended capacitated sustainable transportation problem in a coal mining industry using the analytic hierarchy process (AHP) and data envelopment analysis (DEA) techniques. The AHP technique is used to estimate the weights of different types of vehicles available for transportation on the basis of all three parameters of sustainability, namely economic, environmental, and corporate social responsibility. The DEA technique is used for calculating efficiency scores of vehicles on various routes of the given transportation network using inputs and outputs considered critical in the industrial sector particularly the mining industry. Furthermore, we reduce dependency on carbon based fuels for transportation leading to reduction in greenhouse gas emissions. A fuzzy interactive optimization approach is presented to get preferred compromise transportation solutions including the optimal number of vehicles employed for sustainable transportation. A real-world case of a mining industry in India is discussed to demonstrate applicability of the proposed optimization model and solution method. Moreover, some comparisons are done with existing transportation models in order to present advantages of our approach.
Volume
74
Language
English
OCDE Knowledge area
Minería, Procesamiento de minerales
Scopus EID
2-s2.0-85046708165
Source
Resources Policy
ISSN of the container
03014207
DOI of the container
10.1016/j.resourpol.2018.04.007
Sources of information: Directorio de Producción Científica Scopus