No abstract

No abstract

No abstract

Transportation occupies one-third of the amount in the logistics costs, and accordingly transportation systems largely influence the performance of the logistics system. This work presents an adaptive data-driven innovative modular approach for solving the real-world Vehicle Routing Problems (VRP) in the field of logistics. The work consists of two basic units: (i) an innovative multi-step algorithm for successful and entirely feasible solving of the VRP problems in logistics, (ii) an adaptive approach for adjusting and setting up parameters and constants of the proposed algorithm. The proposed algorithm combines several data transformation approaches, heuristics and Tabu search. Moreover, as the performance of the algorithm depends on the set of control parameters and constants, a predictive model that adaptively adjusts these parameters and constants according to historical data is proposed. A comparison of the acquired results has been made using the Decision Support System with predictive models: Generalized Linear Models (GLM) and Support Vector Machine (SVM). The algorithm, along with the control parameters, which using the prediction method were acquired, was incorporated into a web-based enterprise system, which is in use in several big distribution companies in Bosnia and Herzegovina. The results of the proposed algorithm were compared with a set of benchmark instances and validated over real benchmark instances as well. The successful feasibility of the given routes, in a real environment, is also presented.Keywords Vehicle routing problem  Multi-step algorithm  Data-driven approach  Parameter setting problem  Real-world constraints in logistics

Agile maintenance is the best choice if you want to keep step with your customer needs. It is a result of trying to respond to customer change requests with the high efficiency. High involvement of the customer in the maintenance process is good but also can have negative effects. Change in the behavior of the customer can influence the execution of the change management process or cause the change of the release plan, etc. All that can destabilize normal maintenance velocity and lead to a chaotic relationship with the customer, if not controlled or prevented. This paper describes problems in agile maintenance caused mostly by the change of the customer behavior at the beginning of the economic crisis. It also presents results of the analysis of these problems and recommendations how to identify them and how to prevent them.