Social and Environmental Impact of Advances in Economically Driven Transport Optimization: Case Study in Automobile Distribution

Abstract

Contemporary optimization methods have shown to save costs and increase revenues in many operative fields of application. While human planners tend to focus on parts of the overall problem, these methods use the computational power of modern computers to deeply explore the solution space and thus enable decision-making on a superior level. The methods itself are well explored by the operations research community, where much less is known about their effect on problem aspects that are not directly focused. This study examines the impact of improvements in optimization methods on the economic, social, and environmental dimension within the context of a realistic case in automobile distribution. Two planning methods are compared. The first adapts a step-by-step planning technique typically used by human planners; the second addresses the problem from an overall perspective. The comparison is based on two scenarios. One assumes that a fixed amount of transport orders has to be fulfilled, while the other considers a freight market from which transport opportunities can be freely selected for fulfillment. When the workload is fixed, advancements appear to be beneficial in the economic, social, and environmental dimension at the same time. In contrast the economic dimension is improved disproportionately in the freight market scenario. It can be shown that the objectives of the economic dimension are in conflict to a certain extent with those of the other two dimensions.