Technical Report - Routing a Mixed Fleet of Electric and Conventional Vehicles
now available for download.
In this paper, we propose the Electric Vehicle Routing Problem with Time Windows and Mixed Fleet (E-VRPTWMF) to optimize the routing of a mixed fleet of electric commercial vehicles (ECVs) and conventional internal combustion commercial vehicles (ICCVs). Contrary to existing routing models for ECVs, which assume energy consumption to be a linear function of traveled distance, we utilize a realistic energy consumption model that incorporates speed, gradient and cargo load distribution. This is highly relevant in the context of ECVs because energy consumption determines the maximal driving range of ECVs and the recharging times at stations. To address the problem, we develop an Adaptive Large Neighborhood Search algorithm that is enhanced by a local search for intensification. In numerical studies on newly designed E-VRPTWMF test instances, we investigate the effect of considering the actual load distribution on the structure and quality of the generated solutions. Moreover, we study the influence of different objective functions on solution attributes and on the contribution of ECVs to the overall routing costs. Finally, we demonstrate the performance of the developed algorithm on benchmark instances of the related problems VRPTW and E-VRPTW.
Research areas and current projects
Our research focuses on modeling complex (and often stochastic) search and optimization problems in business, and solving them via computational heuristics. A special emphasis is given to distributed problems arising in social multi-agent systems, which cannot be optimized by pure economic price coordination. Imposing a solution by a central planner will often be rejected by the autonomous agents. We therefore need to design distributed mechanisms providing incentives to participate to the individual agents without deviating too much from a pareto-efficient solution.
We apply these methods to various domains, leading the following complementary areas of research::
- Computational Intelligence
- Vehicle Routing
- Yield Management and Planning of Internal Processes
- Multi-Agent Systems
- Recommender Systems for Reciprocal Matching
- Medical Data Mining and Forecasting
For details please refer to "Research".
Besides our Bachelor courses "Business Information Systems" and "Operations Research" we offer the following Master courses: