Add to ORKGIn this paper, we aim to analyze the performance of some variants of the harmony search (HS) metaheuristic when solving systems of nonlinear equations through the global optimization of an appropriate merit function. The HS metaheuristic draws its inspiration from an artistic process, the improvisation process of musicians seeking a wonderful harmony. A new differential best HS algorithm, based on an improvisation operator that mimics the best harmony and uses a differential variation, is proposed. Computational experiments involving a well-known set of small-dimensional problems are presented. Key words: nonlinear equations, metaheuristic, harmony search
The Harmony Search (HS) draws its inspiration not from a biological or physical process like most ot...
Abstract—This paper proposes two hybrid optimization methods based on Harmony Search algorithm (HS) ...
Harmony Search is a metaheuristic technique for optimizing problems involving sets of continuous or ...
In this paper, we aim to analyze the performance of some variants of the harmony search (HS) metahe...
A multistart (MS) clustering technique to compute multiple roots of a system of nonlinear equations ...
The theoretical analysis of evolutionary algorithms is believed to be very important for understandi...
A multistart (MS) clustering technique to compute multiple roots of a system of nonlinear equations ...
The performance of the Harmony Search (HS) algorithm is highly dependent on the parameter settings a...
Harmony search algorithm (HS) is a new metaheuristic algorithm which is inspired by a process involv...
Harmony search algorithm is the recently developed metaheuristic in the last decade. It mimics the b...
A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in...
Inspired by the improvisation process of music players, a population-based meta-heuristic algorithm-...
AbstractSince the Harmony Search Algorithm (HSA) was first introduced in 2001, it has drawn a world-...
Harmony search algorithm (HSA) is relatively considered as one of the most recent metaheuristic algo...
There exists an analogy between music and optimization. This book focuses on a music-inspired metahe...
The Harmony Search (HS) draws its inspiration not from a biological or physical process like most ot...
Abstract—This paper proposes two hybrid optimization methods based on Harmony Search algorithm (HS) ...
Harmony Search is a metaheuristic technique for optimizing problems involving sets of continuous or ...
In this paper, we aim to analyze the performance of some variants of the harmony search (HS) metahe...
A multistart (MS) clustering technique to compute multiple roots of a system of nonlinear equations ...
The theoretical analysis of evolutionary algorithms is believed to be very important for understandi...
A multistart (MS) clustering technique to compute multiple roots of a system of nonlinear equations ...
The performance of the Harmony Search (HS) algorithm is highly dependent on the parameter settings a...
Harmony search algorithm (HS) is a new metaheuristic algorithm which is inspired by a process involv...
Harmony search algorithm is the recently developed metaheuristic in the last decade. It mimics the b...
A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in...
Inspired by the improvisation process of music players, a population-based meta-heuristic algorithm-...
AbstractSince the Harmony Search Algorithm (HSA) was first introduced in 2001, it has drawn a world-...
Harmony search algorithm (HSA) is relatively considered as one of the most recent metaheuristic algo...
There exists an analogy between music and optimization. This book focuses on a music-inspired metahe...
The Harmony Search (HS) draws its inspiration not from a biological or physical process like most ot...
Abstract—This paper proposes two hybrid optimization methods based on Harmony Search algorithm (HS) ...
Harmony Search is a metaheuristic technique for optimizing problems involving sets of continuous or ...