The paper deals with the problem of production material flow management. The proper way of logistic tasks management has an impact on the production process effectiveness and the cycle time, which is a very important factor in manufacturing. Reducing the production process cycle time results not only in the ability to provide more customers with orders but also in increasing the level of resources usage (machines, operators etc.). In order to reach the aim of improving production effectiveness, the simulation modeling was used. It is a computer method that supports a decision-making process and allows to perform experiments on production without interfering with the real process. The paper also includes a risk analysis performed to evaluate the imperfections of simulation modeling, based on the rules of fuzzy logic.

Improving production processes includes not only activities concerning manufacturing itself, but also all the activities that are necessary to achieve the main objectives. One such activity is transport, which, although a source of waste in terms of adding value to the product, is essential to the realization of the production process. Over the years, many methods have been developed to help manage supply and transport in such a way as to reduce it to the necessary minimum. In the paper, the problem of delivering components to a production area using trains and appropriately laid-out carriages was described. It is a milk run stop locations problem (MRSLP), whose proposed solution is based on the use of heuristic algorithms. Intelligent solutions are getting more and more popular in the industry because of the possible advantages they offer, especially those that include the possibility of finding an optimum local solution in a relatively short time and the prevention of human errors. In this paper, the applicability of three algorithms – tabu search, genetic algorithm, and simulated annealing – was explored.