Heuristics and metaheuristics for biological network alignment: A review
In recent years, with the emergence of big-data and high-throughput biological analyses,
massive biological data have been generated and accessed, and many heuristic and …
massive biological data have been generated and accessed, and many heuristic and …
A decomposition-based many-objective evolutionary algorithm with two types of adjustments for direction vectors
X Cai, Z Mei, Z Fan - IEEE Transactions on Cybernetics, 2017 - ieeexplore.ieee.org
Decomposition-based multiobjective evolutionary algorithm has shown its advantage in
addressing many-objective optimization problem (MaOP). To further improve its …
addressing many-objective optimization problem (MaOP). To further improve its …
Multi-objective optimization for long tail recommendation
Recommender systems are tools to suggest items to target users. Accuracy-focused
recommender systems tend to recommend popular items, while suggesting items with few …
recommender systems tend to recommend popular items, while suggesting items with few …
Decomposition-based-sorting and angle-based-selection for evolutionary multiobjective and many-objective optimization
Multiobjective evolutionary algorithm based on decomposition (MOEA/D) decomposes a
multiobjective optimization problem (MOP) into a number of scalar optimization subproblems …
multiobjective optimization problem (MOP) into a number of scalar optimization subproblems …
MPGAN: Multi Pareto Generative Adversarial Network for the denoising and quantitative analysis of low-dose PET images of human brain
Positron emission tomography (PET) imaging is widely used in medical imaging for
analyzing neurological disorders and related brain diseases. Usually, full-dose imaging for …
analyzing neurological disorders and related brain diseases. Usually, full-dose imaging for …
A benchmark test suite for dynamic evolutionary multiobjective optimization
Growing trend of the dynamic multiobjective optimization research in the evolutionary
computation community has increased the need for challenging and conceptually simple …
computation community has increased the need for challenging and conceptually simple …
A fast community detection algorithm based on reconstructing signed networks
C **a, Y Luo, L Wang, HJ Li - IEEE Systems Journal, 2021 - ieeexplore.ieee.org
Signed networks depict the individual cooperative or hostile relationship in a population,
which can help to deeply mine the characteristics of complex networks and predict the …
which can help to deeply mine the characteristics of complex networks and predict the …
A Survey of Multi-objective Evolutionary Algorithm Based on Decomposition: Past and Future
K Li - IEEE Transactions on Evolutionary Computation, 2024 - ieeexplore.ieee.org
Decomposition has been the mainstream approach in the classic mathematical
programming for multi-objective optimization and multi-criterion decision-making. However …
programming for multi-objective optimization and multi-criterion decision-making. However …
Decomposition multi-objective evolutionary optimization: From state-of-the-art to future opportunities
K Li - arxiv preprint arxiv:2108.09588, 2021 - arxiv.org
Decomposition has been the mainstream approach in the classic mathematical
programming for multi-objective optimization and multi-criterion decision-making. However …
programming for multi-objective optimization and multi-criterion decision-making. However …
Network Community Detection Based on the Physarum-Inspired Computational Framework
C Gao, M Liang, X Li, Z Zhang… - … /ACM transactions on …, 2016 - ieeexplore.ieee.org
Community detection is a crucial and essential problem in the structure analytics of complex
networks, which can help us understand and predict the characteristics and functions of …
networks, which can help us understand and predict the characteristics and functions of …