Supply Sequence Modelling Using Hidden Markov Models

Logistics processes, their effective planning as well as proper management and effective implementation are of key importance in an enterprise. This article analyzes the process of supplying raw materials necessary for the implementation of production tasks. The specificity of the examined waste processing company requires the knowledge about the size of potential deliveries because the delivered waste must be properly managed and stored due to its toxicity to the natural environment. In the article, hidden Markov models were used to assess the level of supply. They are a statistical modeling tool used to analyze and predict the phenomena of a sequence of events. It is not always possible to provide sufficiently reliable information with the existing classical methods in this regard. Therefore, the article proposes modeling techniques with the help of stochastic processes. In hidden Markov models, the system is represented as a Markov process with states that are invisible to the observer but with a visible output (observation) that is a random state function. In the article, the distribution of outputs from the hidden states is defined by a polynomial distribution.

Automated summary

Logistics processes and their effective planning, management, and implementation are crucial for businesses. This article analyzes the process of supplying raw materials for production tasks, specifically in a waste processing company where proper management and storage are necessary due to the toxicity of the waste to the environment. The article proposes the use of hidden Markov models, a statistical modeling tool, to assess the level of supply, as traditional methods may not always provide reliable information. The models represent a system as a Markov process with hidden states and visible outputs, with the distribution of outputs defined by a polynomial distribution.