Vehicle routing optimization for fast-moving consumer goods deliveries in Finland: case Kovanen Logistics

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School of Business | Master's thesis
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Objectives of the Study This research builds a tailored and realistic Vehicle Routing Problem model that includes all the relevant features and constraints for the case company. Using the built model, the research will show the magnitude of cost saving and utilization improvements that the optimization induces. Despite that the Vehicle Routing Problem and its variations are thoroughly covered in literature, its applications, especially on business level, have received little attention. By relaxing and constraining the optimization constraints, the Vehicle Routing Problem can be used to study various business scenarios. This research proposes how the VRP model can be used for strategic, tactical and operational steering of a company specialized in transportation or distribution by introducing a new framework. Academic background and methodology The Vehicle Routing Problem was first introduced by Dantzig and Ramser already in 1959 by the name "Truck Dispatching Problem" and still is one of the most challenging areas of research in the field of Combinatorial Optimization. Data used in this research is real-life case company data and the methodology is a case study. Findings and conclusions The savings potential of optimization proved out to be significant, with savings ranging from 30-40% in subjects such as number of vehicles needed, drive time and distance. These results were used as a basis for discussion on several topics surrounding the Vehicle Routing Problem and logistics optimization in general. Issues such as increasing daily utilization of vehicles and tackling seasonal fluctuations were discussed. Finally, a VeRP-e- STOP framework was introduced, which guides how the VRP can be used for three levels of decision making in companies specialized in transportation and distribution.
Cross-docking, Vehicle Routing Problem, Optimization, Algorithm, Heuristic, Metaheuristic, Fast-Moving Consumer Goods, Trucks, HeuristicLab
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