Yıldız, Ali Rıza2021-03-202021-03-2020130268-37681433-3015http://doi.org/10.1007/s00170-012-4410-yhttps://hdl.handle.net/20.500.12885/1248This paper presents a novel hybrid optimization approach based on teaching-learning based optimization (TLBO) algorithm and Taguchi's method. The purpose of the present research is to develop a new optimization approach to solve optimization problems in the manufacturing area. This research is the first application of the TLBO to the optimization of turning operations in the literature The proposed hybrid approach is applied to two case studies for multi-pass turning operations to show its effectiveness in machining operations. The results obtained by the proposed approach for the case studies are compared with those of particle swarm optimization algorithm, hybrid genetic algorithm, scatter search algorithm, genetic algorithm and integration of simulated annealing, and Hooke-Jeeves patter search.eninfo:eu-repo/semantics/closedAccessHybrid optimizationTeaching-learning based optimization algorithmTaguchi methodManufacturingTurningArticle10.1007/s00170-012-4410-y669-1213191326WOS:000319557200011Q2Q1