Journal ArticleDOI
A Multiobjective Particle Swarm Optimizer Using Ring Topology for Solving Multimodal Multiobjective Problems
Caitong Yue,Boyang Qu,Jing Liang +2 more
TLDR
The algorithm is shown to not only locate and maintain a larger number of Pareto-optimal solutions, but also to obtain good distributions in both the decision and objective spaces.Abstract:
This paper presents a new particle swarm optimizer for solving multimodal multiobjective optimization problems which may have more than one Pareto-optimal solution corresponding to the same objective function value The proposed method features an index-based ring topology to induce stable niches that allow the identification of a larger number of Pareto-optimal solutions, and adopts a special crowding distance concept as a density metric in the decision and objective spaces The algorithm is shown to not only locate and maintain a larger number of Pareto-optimal solutions, but also to obtain good distributions in both the decision and objective spaces In addition, new multimodal multiobjective optimization test functions and a novel performance indicator are designed for the purpose of assessing the performance of the proposed algorithms An effectiveness validation study is carried out comparing the proposed method with five other algorithms using the benchmark functions to prove its effectivenessread more
Citations
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Journal ArticleDOI
Towards augmented kernel extreme learning models for bankruptcy prediction: Algorithmic behavior and comprehensive analysis
Yanan Zhang,Yanan Zhang,Renjing Liu,Ali Asghar Heidari,Ali Asghar Heidari,Xin Wang,Ying Chen,Mingjing Wang,Huiling Chen +8 more
TL;DR: Results for every optimization task demonstrate that LSEOFOA can provide a high-performance and self-assured tradeoff between exploration and exploitation, and overall research findings show that the proposed model is superior in terms of classification accuracy, Matthews correlation coefficient, sensitivity, and specificity.
Journal ArticleDOI
Variable-Size Cooperative Coevolutionary Particle Swarm Optimization for Feature Selection on High-Dimensional Data
TL;DR: The experimental results show that VS-CCPSO has the capability of obtaining good feature subsets, suggesting its competitiveness for tackling FS problems with high dimensionality.
Journal ArticleDOI
An Enhanced Fast Non-Dominated Solution Sorting Genetic Algorithm for Multi-objective Problems
TL;DR: Wang et al. as mentioned in this paper proposed an enhanced fast NSGA-II based on a special congestion strategy and adaptive crossover strategy, which can improve PS distribution and convergence and maintain PF precision.
Journal ArticleDOI
An enhanced fast non-dominated solution sorting genetic algorithm for multi-objective problems
TL;DR: Wang et al. as discussed by the authors proposed an enhanced fast NSGA-II based on a special congestion strategy and adaptive crossover strategy, which can improve PS distribution and convergence and maintain PF precision.
Journal ArticleDOI
Variable-Length Particle Swarm Optimization for Feature Selection on High-Dimensional Classification
TL;DR: This paper proposes the first variable-length PSO representation for FS, enabling particles to have different and shorter lengths, which defines smaller search space and therefore, improves the performance of PSO.
References
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Journal ArticleDOI
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Journal ArticleDOI
The particle swarm - explosion, stability, and convergence in a multidimensional complex space
M. Clerc,James Kennedy +1 more
TL;DR: This paper analyzes a particle's trajectory as it moves in discrete time, then progresses to the view of it in continuous time, leading to a generalized model of the algorithm, containing a set of coefficients to control the system's convergence tendencies.
Journal ArticleDOI
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
Qingfu Zhang,Hui Li +1 more
TL;DR: Experimental results have demonstrated that MOEA/D with simple decomposition methods outperforms or performs similarly to MOGLS and NSGA-II on multiobjective 0-1 knapsack problems and continuous multiobjectives optimization problems.