Mixed Integer Multi-Objective Goal Programming Model For Green Capacitated Vehicle Routing Problem

Abstract

Nowadays, environmental effects of logistics and extensive consumption of natural resources have been given more attention by governments and industries.  Conventionally, these issues and their impact on distribution logistics were not emphasized specifically or addressed directly when solving the Vehicle Routing Problem (VRP). Hence, Green VRP (GVRP) has been introduced to take into consideration both the economic and environmental costs when determining effective routes for distribution services. GVRP is a branch of green logistics in which the externalities of using vehicles, enhancement of transportation effectiveness at operational level, ensuring optimal energy consumption of vehicles, and minimizing fuel consumption are taken into account in the routing and scheduling. This paper presents our study which concerns with formulating a mathematical programming model of Green Capacitated VRP (GCVRP), which focuses are on minimization of the greenhouse gas emissions and fuel consumption, to assuage the resulting effects of transportation on the environment.  The formulated Mixed Integer Goal Programming (MIGP) model has multiple objective functions as its goal, which are minimizing the total distance travelled, minimizing the total fuel consumption and minimizing the total Carbon Dioxide emissions. Two set of benchmark instances have been used to test the proposed model. The MIGP model is solved by the preemptive GP approach and using the MATLAB intlinprog solver.  Based on the computational results, the model has been proven to be able to produce optimal solutions, thus indicating that it has the potential to be applied to real-world VRPs.