Choosing the Optimal Production Strategy by Multi-Objective Optimization Methods

This paper presents the solution of multi-objective optimization of the production process of an automated assembly line model, where combination of conventional mathematical methods and methods of artificial intelligence is used. Paper provides the description of methods used in this process, modifications that were realized in the computational process of NSGA - II evolutionary algorithm as well as the solution of the production process optimization respecting all the defined constraints. The first part of the solution, the definition of the set of non-dominated (Pareto optimal) alternatives, is realized by the modified NSGA - II evolutionary algorithm. From the Pareto optimal solutions, choosing the best solution using various mathematical metrics is presented. Approach for the synthesis of the results obtained from various mathematical metrics used to resolve the task is also mentioned with the scope of objectivization of the optimization process.