INTEGRATION OF COMPUTATIONAL TOOLS TO REDUCE SEARCH SPACE IN MOSO PROBLEMS

In the industrial production scenario, there needs to be synchronization between the logistics flow and the activities to be performed. However, this type of scenario has limited resources, making Discrete Event Simulation able to explore all possibilities, within the limitations found. However, due to the robustness and degree of complexity found, its isolated use is ineffective, since the objectives are conflicting with each other. In this context, the article proposes a method that makes use of Optimization via Multiobjective Simulation, together with Data Envelopment Analysis and Latin Hypercube Design to reduce the search space and determine the best possible solution to the problem found, providing the best limits of variation and high quality solutions. As a result, the method resulted in an average reduction of 79.63% in search space and a variation of 8.8% to 31.18% in computational time.