Quantum-inspired metaheuristic algorithms: comprehensive survey and classification
FS Gharehchopogh - Artificial Intelligence Review, 2023 - Springer
Metaheuristic algorithms are widely known as efficient solutions for solving problems of
optimization. These algorithms supply powerful instruments with significant engineering …
optimization. These algorithms supply powerful instruments with significant engineering …
Multiobjective evolutionary algorithms: A survey of the state of the art
A multiobjective optimization problem involves several conflicting objectives and has a set of
Pareto optimal solutions. By evolving a population of solutions, multiobjective evolutionary …
Pareto optimal solutions. By evolving a population of solutions, multiobjective evolutionary …
Dung beetle optimization algorithm based on quantum computing and multi-strategy fusion for solving engineering problems
F Zhu, G Li, H Tang, Y Li, X Lv, X Wang - Expert Systems with Applications, 2024 - Elsevier
The Dung beetle optimization algorithm is a kind of group intelligence optimization algorithm
proposed by Jiankai Xue in 2022, which has the characteristics of strong optimization …
proposed by Jiankai Xue in 2022, which has the characteristics of strong optimization …
Effect analysis on SOC values of the power lithium manganate battery during discharging process and its intelligent estimation
H Zuo, B Zhang, Z Huang, K Wei, H Zhu, J Tan - Energy, 2022 - Elsevier
In this work, a coupled electrochemical-thermal model of the power lithium manganate
battery under discharging process is established and verified, and its maximum surface …
battery under discharging process is established and verified, and its maximum surface …
Optimal energy management of microgrids using quantum teaching learning based algorithm
Quantum inspired computational intelligence is gaining momentum in the interest of
enhancing the performance of existing metaheuristic optimization while solving multi …
enhancing the performance of existing metaheuristic optimization while solving multi …
Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
This paper proposes a novel evolutionary algorithm inspired by quantum computing, called
a quantum-inspired evolutionary algorithm (QEA), which is based on the concept and …
a quantum-inspired evolutionary algorithm (QEA), which is based on the concept and …
An optimization spiking neural P system for approximately solving combinatorial optimization problems
Membrane systems (also called P systems) refer to the computing models abstracted from
the structure and the functioning of the living cell as well as from the cooperation of cells in …
the structure and the functioning of the living cell as well as from the cooperation of cells in …
Enhanced Harris hawks optimization with multi-strategy for global optimization tasks
CY Li, J Li, HL Chen, M **, H Ren - Expert Systems with Applications, 2021 - Elsevier
Abstract Harris Hawks Optimization (HHO) algorithm is a newly proposed meta-heuristic
optimization algorithm that simulates the hunting process of the Harris hawks. It has the …
optimization algorithm that simulates the hunting process of the Harris hawks. It has the …
Quantum-inspired evolutionary algorithms with a new termination criterion, H/sub/spl epsi//gate, and two-phase scheme
From recent research on combinatorial optimization of the knapsack problem, quantum-
inspired evolutionary algorithm (QEA) was proved to be better than conventional genetic …
inspired evolutionary algorithm (QEA) was proved to be better than conventional genetic …
Machine learning algorithms in quantum computing: A survey
SB Ramezani, A Sommers… - … joint conference on …, 2020 - ieeexplore.ieee.org
Machine Learning (ML) aims at designing models that learn from previous experience,
without being explicitly formulated. Applications of machine learning are inexhaustible …
without being explicitly formulated. Applications of machine learning are inexhaustible …