D Zhan, H Xing - Journal of Global Optimization, 2020 - Springer
The expected improvement (EI) algorithm is a very popular method for expensive optimization problems. In the past twenty years, the EI criterion has been extended to deal …
Complex continuous optimization problems widely exist nowadays due to the fast development of the economy and society. Moreover, the technologies like Internet of things …
Abstract Generally, Synthetic Benchmark Problems (SBPs) are utilized to assess the performance of metaheuristics. However, these SBPs may include various unrealistic …
M Kaur, D Singh, V Kumar, BB Gupta… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
This paper proposes a secure and energy-efficient Internet of Things (IoT) model for e- health. The main objective is to secure the transmission and retrieval of biomedical images …
Over the last three decades, a large number of evolutionary algorithms have been developed for solving multi-objective optimization problems. However, there lacks an upto …
L Ma, N Li, Y Guo, X Wang, S Yang… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
The performance of decomposition-based algorithms is sensitive to the Pareto front shapes since their reference vectors preset in advance are not always adaptable to various problem …
Y Sun, GG Yen, Z Yi - IEEE Transactions on Evolutionary …, 2018 - ieeexplore.ieee.org
Inverted generational distance (IGD) has been widely considered as a reliable performance indicator to concurrently quantify the convergence and diversity of multiobjective and many …
Decomposition is a well-known strategy in traditional multiobjective optimization. However, the decomposition strategy was not widely employed in evolutionary multiobjective …
Although synthetic test problems are widely used for the performance assessment of evolutionary multi-objective optimization algorithms, they are likely to include unrealistic …