Layout Optimization for Cognitive Material Flow Systems
The lack of flexibility in today's logistics motivates the development of novel transportation systems. In this work, I address the question of optimal integration of such novel transportation systems into existing production facilities. The challenge is to simultaneously consider several conflicting objective values at the same time. For this purpose, a comprehensive mathematical model of a transportation system is created from available input parameters. Subsequently, two optimization methods (the Genetic Algorithm and Simulated Annealing) are developed and implemented.