This paper presents the Clustering Search (CS) as a new hybrid metaheuristic, which works in conjunction with other metaheuristics, managing the implementation of local search algorithms for optimization problems. Usually the local search is costly and should be used only in promising regions of the search space. The CS assists in the discovery of these regions by dividing the search space into clusters. The CS and its applications are reviewed and a case study for a problem of capacitated clustering is presented.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Universidade Federal do MaranhãoUniversidade Federal de São Paulo (UNIFESP)Instituto Nacional de Pesquisas EspaciaisUNIFESPSciEL
In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRA...
Designing and modeling an optimization algorithm with dedicated search is a costly process and it ne...
Metaheuristic algorithms are often trapped in local optimum solutions when searching for solutions. ...
This paper presents the Clustering Search (CS) as a new hybrid metaheuristic, which works in conjunc...
The Capacitated Centered Clustering Problem (CCCP) consists of defining a set of p groups with minim...
Abstract: We consider clustering as a combinatorial optimisation problem. Local search provides a si...
This paper approaches a recent hybrid evolutionary algorithm, called Evolutionary Clustering Search ...
Metaheuristic algorithms are often trapped in local optimum solutions when searching for solutions. ...
As the storage capacity and the processing speed of search engine is growing to keep up with the con...
Several practical applications require joining various rankings into a consensus ranking. These appl...
As the storage capacity and the processing speed of search engine is growing to keep up with the con...
In this paper, we investigate application of various options of algorithms with greedy ...
In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRA...
In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRA...
In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRA...
In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRA...
Designing and modeling an optimization algorithm with dedicated search is a costly process and it ne...
Metaheuristic algorithms are often trapped in local optimum solutions when searching for solutions. ...
This paper presents the Clustering Search (CS) as a new hybrid metaheuristic, which works in conjunc...
The Capacitated Centered Clustering Problem (CCCP) consists of defining a set of p groups with minim...
Abstract: We consider clustering as a combinatorial optimisation problem. Local search provides a si...
This paper approaches a recent hybrid evolutionary algorithm, called Evolutionary Clustering Search ...
Metaheuristic algorithms are often trapped in local optimum solutions when searching for solutions. ...
As the storage capacity and the processing speed of search engine is growing to keep up with the con...
Several practical applications require joining various rankings into a consensus ranking. These appl...
As the storage capacity and the processing speed of search engine is growing to keep up with the con...
In this paper, we investigate application of various options of algorithms with greedy ...
In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRA...
In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRA...
In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRA...
In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRA...
Designing and modeling an optimization algorithm with dedicated search is a costly process and it ne...
Metaheuristic algorithms are often trapped in local optimum solutions when searching for solutions. ...