Practical conditions in the optimization of shipment delivery processes

The number of factors influencing the efficiency of logistics and transport processes makes finding an optimal solution to a given decision-making problem very difficult. For this reason, models are being developed that enable finding a near-optimal solution. IT tools are a great help in decision-making. Regardless, however, of whether we are talking about a mathematical model in analytical form or its implementation in a computer program, the practical conditions under which transport processes are carried out must be taken into account. Only then can these models be practically adopted as a reflection of real logistics systems.This article is devoted to taking these conditions into account in various types of models.
The considerations are conducted from the perspective of entities providing transport, forwarding, and logistics services.
INTRODUCTION
Transport processes, including goods delivery processes, are very difficult to organize and manage in such a way that their economic efficiency is as high as possible. The transport process is influenced by many different factors, largely external and independent of the entities carrying out these processes. For this reason, it is difficult to find optimal solutions regarding the transport of goods and to model processes in such a way that, on the one hand, these models correspond to reality, and on the other, constitute a useful tool for decision-making in practice. In other words, such models should be user-friendly for employees without academic knowledge, while at the same time allowing for the resolution of often complex decision-making problems. Setting such requirements for decision-making models creates a kind of
“tension” – on the one hand, the complexity of transport issues encourages the development of optimization methods that are intended to improve decision-making processes. On the other hand, this very complexity creates a temptation to simplify models. However, there is a certain limit to such simplification, beyond which models no longer have a connection to reality, and although they simplify decision-making, these decisions may be sub-optimal. (…)

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