Convergence

Surrogate-Assisted Cooperative Swarm Optimization of High-Dimensional Expensive Problems
Surrogate models have shown to be effective in assisting metaheuristic algorithms for solving computationally expensive complex …
Chaoli Sun, Yaochu Jin, Ran Cheng, Jinliang Ding, Jianchao Zeng
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A Multi-objective Evolutionary Algorithm Based on an Enhanced Inverted Generational Distance Metric
As a pivotal component in multi-objective evolutionary algorithms (MOEAs), the environmental selection determines the quality of …
Ye Tian, Xingyi Zhang, Ran Cheng, Yaochu Jin
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A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization
In evolutionary multiobjective optimization, maintaining a good balance between convergence and diversity is particularly crucial to …
Ran Cheng, Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
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A Competitive Swarm Optimizer for Large Scale Optimization
In this paper, a novel competitive swarm optimizer (CSO) for large scale optimization is proposed. The algorithm is fundamentally …
Ran Cheng, Yaochu Jin
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A Multi-swarm Evolutionary Framework based on a Feedback Mechanism
Most evolutionary algorithms, including particle swarm optimization (PSO) algorithms, involve at least one population (swarm) to …
Ran Cheng, Chaoli Sun, Yaochu Jin
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Simulating Swarm Behaviuors for Optimisation by Learning from Neighbours
Competitive particle swarm optimizer (ComPSO) is a novel swarm intelligence algorithm that does not need any memory. Different from the …
Ran Cheng, Yaochu Jin
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