American Journal of Engineering Research (AJER) 2016 American Journal of Engineering Research (AJER) e-ISSN: 2320-0847 p-ISSN : 2320-0936 Volume-5, Issue-8, pp-294-299 www.ajer.org Research Paper Open Access www.ajer.org Page 294 An Analytical Model Formulation To Enhance The Green Logistics (GL) Operations: From The Perspective Of Vehicle Routing Problem (VRP) Reshani P. Liyanage 1 , Thashika D. Rupasinghe 1 1 (Department of Industrial Management, University of Kelaniya, Sri Lanka) ABSTRACT : This paper is focused on the growing need of integrating environmentally sound choices into supply-chain management. The concept of green economic practices driven by the environmental sustainability challenges posed the concept of green logistics, to evolve in the last few decades.To establish the field further, the purpose of this paper is twofold. First, it offers anextensive systematic review of literature on GL with a critical review of the studies that have been considered in the paper.Second, it offers a conceptual analytical model where the canonical capacitated vehicle routing problem is extended to add the measures of Carbon Dioxide (CO 2 ) emissions. The proposed, multi objective optimization model tackles the conflicting objectives of CO 2 emission reduction and cost minimization. The developed generic model integrates the traffic information in providing the user with opportunity to have more realistic solution. The model also enables strategic decision making to improve the GL operations while allowing greatercompetitive advantage. Keywords: Analytical Modelling, CO 2 emission reduction, Green Logistics I. INTRODUCTION As globalization makes the world become smaller, it becomes increasingly easy to see how the lives of human everywhere are closely synced up with one another. Due to the rapid industrialization, environment pollution happens at an increased pace [1]. This has led to many adverse implications such as increase in temperature and scarcity of resources. These issues have built awareness among consumers and stringent laws that are more environment conscious [2]. This increased consumer awareness, legislations, standards on environment such as ISO 14001,competitiveness, external influencers and greater concern on environment have pushed environmental issues into the spotlight, making it imperative for organizations to have a plan of action for “going green” [3]. Proactive companies are reaping benefits in the form of cost savings, favorable public opinion and access to clean-energy stimulus funds. Meanwhile, laggards risk expensive consequences since they will lose the market share as environmentally conscious buyers continue to vote with their money [3]. Within the past few decades, the concept of “Going Green” became popular among the practitioners and researchers. So when it comes to Supply Chain Management (SCM), a new area known as Green Supply Chain Management (GSCM) was emerged [4]. Among the activities of a typical SCM, transport and logistics have a greater impact on the environment making GL to become a significant area of study [4]. Through the analysis of literature, it could be seen that many researchers had focused their attention to the areas of carbon foot-print reduction and energy conservation through vehicle routing, scheduling and network optimization, reverse logistics, and waste disposal pertaining to Green Logistics (GL) [5]–[9]. Literature highlights, that techniques such as, simulation modelling, mixed integer programming, multi- objective linear programming, Lagrange relaxation, genetic algorithm-based heuristics, fuzzy mathematical programming modelling methods etc. have been used to model the aforementioned aspects [7], [10], [11]. Table 1 gives the critical review of the modelling techniquesused in the studies which consider CO 2 emission reduction and have the VRP perspective in it. The Table 2 shows the critical review of the modelling techniques of the studies which do not have the VRP perspective in it.