Cinthia Peraza

  • Citations Per Year
Learn More
Abstract: In this paper, a new fuzzy harmony search algorithm (FHS) for solving optimization problems is presented. FHS is based on a recent method using fuzzy logic for dynamic adaptation of the harmony memory accepting (HMR) and pitch adjustment (PArate) parameters that improve the convergence rate of traditional harmony search algorithm (HS). The(More)
In this paper we propose a new method based on an interval type-2 fuzzy logic system for dynamic parameter adaptation in the harmony search (HS) algorithm. The main contribution of this paper is an improvement of HS in its abilities to search in a global and local fashion, by dynamically changing some of its parameters using an interval type-2 fuzzy logic(More)
This article focuses on the dynamic parameter adaptation in the harmony search algorithm using Type-1 and interval Type-2 fuzzy logic. In particular, this work focuses on the adaptation of the parameters of the original harmony search algorithm. At present there are several types of algorithms that can solve complex real-world problems with uncertainty(More)
This paper develops a new fuzzy harmony search algorithm (FHS) for solving optimization problems. FHS employs a novel method using fuzzy logic for adaptation of the harmony memory accepting parameter that enhances the accuracy and convergence rate of the harmony search (HS) algorithm. In this paper the impacts of constant parameters on harmony search(More)
  • 1