Multi-clustering via evolutionary multi-objective optimization

DOI10.1016/j.ins.2018.03.047zbMath1440.68244OpenAlexW2794136136WikidataQ130109363 ScholiaQ130109363MaRDI QIDQ2195342

Li-Ning Xing, Hisao Ishibuchi, Shiming Lai, Rui Wang, Ling Wang, Guo-Hua Wu

Publication date: 8 September 2020

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2018.03.047

zbMATH Keywords

multi-objective optimizationclusteringevolutionary algorithms

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Multi-objective and goal programming (90C29) Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (5)

Multi-objective soft subspace clustering in the composite kernel space ⋮ Constrained optimization for stratified treatment rules with multiple responses of survival data ⋮ A multi-objective memetic algorithm for low rank and sparse matrix decomposition ⋮ Multi-objective evolutionary algorithm with prediction in the objective space ⋮ A novel many-objective evolutionary algorithm based on transfer matrix with kriging model

Uses Software

• MOEA/D

Cites Work

• Unnamed Item
• Preference-inspired co-evolutionary algorithms using weight vectors
• The iPICEA-g: a new hybrid evolutionary multi-criteria decision making approach using the brushing technique
• Cardinality constrained combinatorial optimization: complexity and polyhedra
• A multi-population cooperative coevolutionary algorithm for multi-objective capacitated arc routing problem
• Large scale evolutionary optimization using cooperative coevolution
• Evolutionary Algorithms for Solving Multi-Objective Problems

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