In the master thesis we developed methods for optimizing tasks assignment in high bay warehouse system. Optimization was performed based on a real warehouse system from which we acquired all specifications. In our optimization we took into account all physical properties of the warehouse from the specification.
Warehouse device for moving transport storage units in the selected warehouse can move two transport units at the same time, giving us a lot of optimization options.
To optimize tasks assignment we used Dijkstra algorithm, Bellman-Ford algorithm, genetic algorithm, ant colony optimization algorithm, algorithm A* and neighborhood algorithm.
We achieved the best result using neighborhood algorithm based on decision-making approach. Optimization of five hundred tasks was done in less than one second, and with it we increased task execution speed by 20 % and optimized energy consumption by 40 % .