Educational Competition Optimization (ECO), as a new metaheuristic algorithm, performs well in single-objective optimization problems, but it is difficult to apply to multi-objective complex optimization problems. Hence, a Multi-Objective Educational Competition Optimization (MOECO) based on the Pareto improvement and the roulette strategy is proposed. In order to verify the effect of MOECO in engineering application, MOECO was used to solve the hobbing control parameter optimization model. Compared with the Multi-Objective Gray Wolf Algorithm (MOGWO) and the Multi-Objective Runge Kutta Optimizer (MORUN), the experimental results show that MOECO is feasible and effective in this engineering case. MOECO provides a new solution for complex multi-objective optimization problems, which has theoretical value and engineering application potential.
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