Multi-criteria optimization of the water jet cutting process using the MOEA algorithm

The article explores multi-objective optimization problems (MOOP) commonly encountered in engineering scenarios, focusing specifically on optimizing waterjet abrasive cutting. It uses an evolutionary algorithm (Multi-Objective Evolutionary Algorithm - MOEA) to optimize key process parameters such as maximum cutting depth and minimal roughness. The article presents a mathematical model of multi-criteria methods and discusses Pareto optimality as necessary to solve multiple conflicting objectives. The research utilized MOEA, operating on evolution and natural selection principles, to find Pareto-efficient solutions that balance the trade-offs between objectives. The results included various simulations showing how different settings of parameters like abrasive mass flow rate, pressure, and traverse speed affected the outcomes.