Management Decision-Making for Logistics Systems Using a Fuzzy-Neural Simulation

The chapter presents a management decision-making approach of logistics aspects in port during interactions between two kinds of transport. The described methodology is developed according to Industry 4.0 concept. Therefore, decisions are made based on smart methods used to obtain forecast values of cargo transshipment volumes. The methodology involves taking into account two restrictions related to technical peculiarities of the internal port infrastructure and technological aspects of the interaction between two kinds of transport. The hybrid neuro-fuzzy ANFIS system is used as a predictor. Time series values were previously selected from the retrospective sample in order to set up a fuzzy-neural model. These demand values are most informative and fully describe the current trends of grain cargo transshipments. The average prediction error does not exceed 4.99%. The actual capacity is calculated for overloading mechanisms in the port according to forecast. The formation of final management decisions was made after calculation of the necessity port capacity to ensure coordinated operation of trucks and loading mechanisms. The rational area of management decision-making in the organization of logistics systems operation in the port is defined. Mathematical formalization of further research aimed at minimization of ship service time in port is presented.