In this paper, we use a recently proposed algorithm-novel global harmony search (NGHS) algorithm to solve unconstrained problems. The NGHS algorithm includes two important operations: position updating and genetic mutation with a low probability. The former can enhance the convergence of the NGHS, and the latter can effectively prevent the NGHS from being trapped into the local optimum. Based on a large number of experiments, the NGHS has demonstrated stronger convergence and stability than original harmony search (HS) algorithm and its two improved algorithms (IHS and SGHS)
Harmony search algorithm is the recently developed metaheuristic in the last decade. It mimics the b...
For the purpose of enhancing the search ability of the cuckoo search (CS) algorithm, an improved rob...
In this work, a new version of the Harmony Search algorithm for solving multi-objective optimization...
A novel global harmony search (NGHS) algorithm, as proposed in 2010, is an improved algorithm that c...
Inspired by the swarm intelligence of particle swarm, a novel global harmony search algorithm (NGHS)...
The performance of the Harmony Search (HS) algorithm is highly dependent on the parameter settings a...
In order to better solve discrete 0-1 knapsack problems, a novel global-best harmony search algorith...
The theoretical analysis of evolutionary algorithms is believed to be very important for understandi...
Abstract—This paper proposes two hybrid optimization methods based on Harmony Search algorithm (HS) ...
In this paper, we propose an improved harmony search algorithm named LHS with three key features: (i...
A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in...
Harmony search (HS) method is an emerging metaheuristic optimization algorithm. In this paper, an im...
AbstractSince the Harmony Search Algorithm (HSA) was first introduced in 2001, it has drawn a world-...
An adaptive harmony search algorithm utilizing differential evolution and opposition-based learning ...
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...
For the purpose of enhancing the search ability of the cuckoo search (CS) algorithm, an improved rob...
In this work, a new version of the Harmony Search algorithm for solving multi-objective optimization...
A novel global harmony search (NGHS) algorithm, as proposed in 2010, is an improved algorithm that c...
Inspired by the swarm intelligence of particle swarm, a novel global harmony search algorithm (NGHS)...
The performance of the Harmony Search (HS) algorithm is highly dependent on the parameter settings a...
In order to better solve discrete 0-1 knapsack problems, a novel global-best harmony search algorith...
The theoretical analysis of evolutionary algorithms is believed to be very important for understandi...
Abstract—This paper proposes two hybrid optimization methods based on Harmony Search algorithm (HS) ...
In this paper, we propose an improved harmony search algorithm named LHS with three key features: (i...
A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in...
Harmony search (HS) method is an emerging metaheuristic optimization algorithm. In this paper, an im...
AbstractSince the Harmony Search Algorithm (HSA) was first introduced in 2001, it has drawn a world-...
An adaptive harmony search algorithm utilizing differential evolution and opposition-based learning ...
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...
For the purpose of enhancing the search ability of the cuckoo search (CS) algorithm, an improved rob...
In this work, a new version of the Harmony Search algorithm for solving multi-objective optimization...