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Air-bearing surface (ABS) designs that satisfy very strict multiobjective goals are of great importance for magnetic hard disk drives. Finding such optimal designs is a strongly nonlinear problem. In slider ABS optimization, the evaluation of the objective function for every sample design takes substantial computation time. It is desirable to reduce the number of sample designs evaluated without losing the global property of the optimization algorithm. In this paper, the DIRECT (DIviding RECTangle) optimization technique, which is a deterministic global optimization technique, was applied to slider ABS optimization. Results show that the DIRECT algorithm has a very fast convergence rate and it outperforms the adaptive simulated annealing algorithm.