Adaptive multi-phase approach for solving the realistic vehicle routing problems in logistics with innovative comparison method for evaluation based on real GPS data.

Transportation management, as a part of the supply chain management, is a complex process that consists of planning and delivering goods to customers. The paper presents a complete multi-phase intelligent and adaptive transportation management system, which includes data collection, parameter tuning, and the heuristic algorithm based on the Tabu search for vehicle routing. The paper describes the procedure for collecting Global Positioning System (GPS) data and analyzing the compliance with the proposed routes based on the data collected. The described routing algorithm is powerful and supports many real-world limitations. An algorithm for the anomaly detection in the GPS data is presented as well as the usage of collected GPS data to improve the future results of the algorithm. The concept was implemented and tested on real data in some of the largest distribution companies in Bosnia and Herzegovina. The proposed approach resulted with more than satisfactory results in real-world application. [ABSTRACT FROM AUTHOR]