A multiobjective optimization algorithm for multifactor air bearing design

This study extends a new optimization algorithm, group inching fortification (GIF) method, to solve an air bearing problem. The air bearing design problem consists of four design factors and the goal is to satisfy two objectives simultaneously. In the GIF method the initial group of designs in Pareto rank 1 is used as the basis to inch up the formation of Pareto solution set, which is fortified over the search process by uniting superior or non-dominated solutions from base-point exploration moves. The search of the original GIF method is terminated when all the initial designs are in the rank 1 of Pareto curve in the criterion space. In this study, an exploration move of the end points of Pareto curve is suggested. This can generate a better quality of Pareto curve and/or increase the coverage (breadth) of the Pareto curve, which is essential for many bearing or engineering design applications. This study provides an easy-to-implement multiobjective optimization technique to solve tribological designs efficiently.