Performance Evaluation of Modified Adaptive Tabu Search Algorithms and Its Application

Abstract

Abstract

This paper presents a modified Adaptive Tabu Search Algorithm, namely mATS by adding an adaptive neighborhood
mechanism under the main purpose enhancing search potential of ATS. An application of mATS to the real world problem is to
solving the parameter identification problem of frequency modulation sounds (FMS) which is multimodal and also hard to solveby classical methods. Performance evaluations are elaborated with three surface optimization functions, Bohachevsky’s, Rastrigin’s and Shekel’s foxholes. From the performance test, the results showed that the mATS were faster than those of the original ATS. Moreover, the proposed mATS approach obtained the better quality of the optimal solution than any other methods
of previous works.