Incorporating Expert Knowledge in Decision Support for Logistics: Balancing Costs and Customer Relations

Decision support within transport companies should not only use traditional objective functions, but also reason about qualitative effects on all involved actors. We propose a fuzzy logic rule base that can be used in addition to traditional operation research tools to calculate not just optimal solutions, but solutions that are optimal with respect to knowledge about the preferences and long-term effects on customers, employees, and the environment. We propose a fuzzy logic based judge module that is capable of evaluating logistical performance considering all parties involved in the act transporting a container. It is based on measurements of selected key performance indicators that are fuzzified and combined into satisfaction scores of customers, employees and society. Our proposed method not only enables the continuity of the quality of planning by storing and maintaining valuable expert knowledge, but can also explain decisions based on this knowledge