Vehicle fuel consumption minimization in routing over-dimensioned and overweight trucks in capacitated transportation networks

Abstract

Pollutants such as carbon monoxide, hydrocarbons and particulates (black soot) are released from vehicle exhaust, affecting the quality of the air and contributing to another environmental problem known as the greenhouse effect. Fuel consumption and pollution effects increase with travel distances and account for a large portion of transportation costs. State Departments of Transportation must issue permits to allow trucking companies to use their highway networks for their over-sized vehicles and must provide a safe route in just a few minutes. Highway networks in a state include roads of varying widths, turns that may be infeasible for large or long vehicles, bridges with insufficient weight carrying capacities for very heavy trucks, and underpasses that limit the height of tall trucks. This article proposes a procedure for finding a maximum-capacity path subject to a length constraint that excludes routes that may be exceedingly long to be considered environment-friendly and cost-effective. Traditional procedures to find a route do not have the capability to identify constrained paths. The paper formulates a linear-integer programming model and uses an arc-elimination procedure to identify the optimal route with maximal capacity while satisfying the length constraint. Constrained maximum-capacity paths are identified by iteratively using a revised shortest-path algorithm. Different types of capacities such as weight, width, and height restrictions are explicitly considered in the proposed methodology. To address the turn restriction, a transformation approach is designed to convert the original network with penalty turns into an equivalent one without such penalties. After that, an arc-elimination procedure is applied on the transformed network for optimizing the problem. The proposed approach is found to be efficient when tested using the Tennessee highway network. The case study shows insights on choosing the routes considering the different types of capacities and balancing route capacity and lengths.