Hybrid Multi-Objective Optimization Methods for Client-Centered Logistics

Client-centered logistics problems appear in many highly relevant areas of our daily life. They range from the design of public transportation networks to field workforce scheduling in private service companies. Many of these problems have in common that, besides a cost-oriented objective, there also exists a user-centered objective. Theses two goals are usually contradicting: lower costs lead to lower quality of service and vice versa. The respective decision makers are confronted with the task of assigning weights to the different objectives, representing their respective preferences. A compromise solution, computed based on these weights, lacks important additional information. This information concerns the tradeoff between costs and quality of service: would higher quality of service be possible at only little additional cost? One possibility to circumvent this problem consists in the application of multi-objective optimization methods. These methods do not only generate a single compromise solution but a whole set of acceptable compromise solutions. They thus allow the decision maker to choose the appropriate solution out of a whole set of solutions. In this project, innovative solution methods, which will be applicable to a large class of logistics problems with multiple objectives, will be developed.