An Optimization Model on Fleet Size and Mixed Vehicle Routing Problem Considering CO2 Emissions Cost and Its Algorithm

Abstract

Logistics activity is both a major energy consumption user and an important CO₂ emission source. As logistics service activity rises in the city, it is crucial to improve the efficiency of fuel usage, as well as decrease the CO₂ emission of unit shipment using vehicle routing optimization. Based on the analysis of the characteristics of energy consumption and emission factors of CO₂ in the vehicle routing problem with multiple vehicles, this paper investigates the problem of fleet size and mixed vehicle routing problem considering CO₂ emissions cost (Green Fleet Size and Mixed Vehicle Routing Problem, G-FSMVRP ). A heuristic algorithm based on a genetic algorithm is given. Finally, a numerical simulation example is given to illustrate the optimization model and its algorithm. The findings show that: (1) the shortest route does not necessarily produce the least energy consumption; (2) compared with the traditional vehicle routing (based on shortest path), vehicle routing considering CO₂ emissions has a lower total cost, but longer distance travelled; and, (3) the genetic algorithm is an effective algorithm to solve the green vehicle routing problem.