TY - JOUR
T1 - AN OPTIMISATION MODEL FOR SUSTAINABLE MULTI-COMMODITY TRANSPORTATION PLANNING
AU - Aggarwal, Usha
AU - Mehlawat, Mukesh Kumar
AU - Gupta, Pankaj
AU - Charles, Vincent
N1 - Publisher Copyright:
© The authors. Published by EDP Sciences, ROADEF, SMAI 2024.
PY - 2024/3/1
Y1 - 2024/3/1
N2 - This paper aims to establish a supply chain model that significantly reduces economic and environmental costs. It comprises all activities related to procurement, production, and distribution planning. The proposed multi-objective multi-commodity optimisation model deals with the four conflicting objectives of reducing costs and emissions and choosing top-priority suppliers and the most efficient vehicles. We apply an integrated AHP (analytic hierarchy process) and TOPSIS (technique for order preference by similarity to an ideal solution) technique to determine the weights of suppliers, depending on three indices of criteria, alternatives, and raw material. This paper proposes a cross-efficiency evaluation method using data envelopment analysis (DEA) to ensure that the cross-evaluation of different types of vehicles for evaluating peers is as consistent as possible. The mutually contradictory objectives give rise to several Pareto-optimal solutions. The optimal compromise solutions are found using a lexicographic goal programming technique. We present a real-world case to demonstrate the effectiveness of the proposed methodology, followed by numerical comparisons and additional insights.
AB - This paper aims to establish a supply chain model that significantly reduces economic and environmental costs. It comprises all activities related to procurement, production, and distribution planning. The proposed multi-objective multi-commodity optimisation model deals with the four conflicting objectives of reducing costs and emissions and choosing top-priority suppliers and the most efficient vehicles. We apply an integrated AHP (analytic hierarchy process) and TOPSIS (technique for order preference by similarity to an ideal solution) technique to determine the weights of suppliers, depending on three indices of criteria, alternatives, and raw material. This paper proposes a cross-efficiency evaluation method using data envelopment analysis (DEA) to ensure that the cross-evaluation of different types of vehicles for evaluating peers is as consistent as possible. The mutually contradictory objectives give rise to several Pareto-optimal solutions. The optimal compromise solutions are found using a lexicographic goal programming technique. We present a real-world case to demonstrate the effectiveness of the proposed methodology, followed by numerical comparisons and additional insights.
KW - DEA technique
KW - Sustainable supply chain
KW - TOPSIS technique
KW - mixed-integer decision problem
KW - multi-commodity transportation
KW - multi-objective optimisation
UR - http://www.scopus.com/inward/record.url?scp=85191028952&partnerID=8YFLogxK
U2 - 10.1051/ro/2024049
DO - 10.1051/ro/2024049
M3 - Article
AN - SCOPUS:85191028952
SN - 2804-7303
VL - 58
SP - 1835
EP - 1869
JO - RAIRO - Operations Research
JF - RAIRO - Operations Research
IS - 2
ER -