Stochastic algorithms in multimodal 3PL segment for the digital environment

This paper discusses the problem of creation of control algorithms when working in the Third Party Logistic concept. It considers the process of supply management when several means of transport and an intermediate distribution center are used. It is assumed that goods are processed in the Machine-to-Machine mode by means of machine-readable codes. The controlling server processes the data and makes a decision either to use one or another mode of transport, or to store the cargo temporarily at the distribution center. An option is provided when an emergent stock of a limited y is placed directly at the end point so that the impact of market uncertainty in demand can be mitigated. The methods of mathematical modeling in the time of uncertainty of the operational environment are applied. The algorithm is based on the stochastic programming method. The practical focus of the work lies in orienting the results on multimodal logistics, which makes the model scalable. The computations, which use the algorithms developed in the paper, provide commercial network managers with a convenient tool for planning current activities taking into account market uncertainty in all operations, when dealing both with consumers and suppliers throughout the business chain, including distribution centers as independent nodes of machine-to-machine interaction. The implementation of the proposed models not only will bring economic benefits and reduce the global traffic, but will also help improve the environment and give a significant social effect.