A novel MOALO-MODA ensemble approach for multi-objective optimization of machining parameters for metal matrix composites

Machining of metal matrix composites (MMCs) has now become an essential task in shaping them to their final usable forms for various industrial applications. These machining operations may range from drilling simple through holes cutting and the into complex shapes. Determination optimal process parameters during presents a combinatorial optimization problem, which turn out be more due involvement material dependent MMCs, like particle size, reinforcement percentage etc. The importance increases manifold conflicting settings different attaining desired quality characteristics. In this paper, two nature-inspired algorithms, i.e. multi-objective antlion (MOALO) dragonfly algorithm (MODA) are applied MMCs. To mitigate uncertainties global optimality predicted Pareto fronts arising stochastic nature metaheuristics, ensemble approach integrating MOALO MODA techniques is proposed here. It demonstrated with help case studies that MOALO-MODA far superior its individual counterparts thus, can employed development robust reliable fronts.