Hybrid evolutionary algorithm for the Capacitated Centered Clustering Problem

Authors:
Antonio Augusto Chaves;Luiz Antonio Nogueira Lorena
Affiliations:
Department of Mathematics, São Paulo State University, Guaratinguetá, Brazil;Laboratory of Computing and Applied Mathematics, National Institute for Space Research, São José dos Campos, Brazil
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 6
Cited 1

Variable neighborhood search

Computers and Operations Research
Uniform Crossover in Genetic Algorithms

Proceedings of the 3rd International Conference on Genetic Algorithms
Clustering search algorithm for the capacitated centered clustering problem

Computers and Operations Research
The capacitated centred clustering problem

Computers and Operations Research
Evolutionary clustering search for flowtime minimization in permutation flow shop

HM'07 Proceedings of the 4th international conference on Hybrid metaheuristics
Hybrid metaheuristic for the prize collecting travelling salesman problem

EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization

Clustering search heuristic for solving a continuous berth allocation problem

EvoCOP'12 Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization

Quantified Score

Hi-index	12.05

Visualization

Abstract

The Capacitated Centered Clustering Problem (CCCP) consists of defining a set of p groups with minimum dissimilarity on a network with n points. Demand values are associated with each point and each group has a demand capacity. The problem is well known to be NP-hard and has many practical applications. In this paper, the hybrid method Clustering Search (CS) is implemented to solve the CCCP. This method identifies promising regions of the search space by generating solutions with a metaheuristic, such as Genetic Algorithm, and clustering them into clusters that are then explored further with local search heuristics. Computational results considering instances available in the literature are presented to demonstrate the efficacy of CS.