An improved reptile search algorithm with ghost opposition-based learning for global optimization problems
In 2021, a meta-heuristic algorithm, Reptile Search Algorithm (RSA), was proposed. RSA
mainly simulates the cooperative predatory behavior of crocodiles. Although RSA has a fast …
mainly simulates the cooperative predatory behavior of crocodiles. Although RSA has a fast …
Fitness-Distance-Constraint (FDC) based guide selection method for constrained optimization problems
In the optimization of constrained type problems, the main difficulty is the elimination of the
constraint violations in the evolutionary search process. Evolutionary algorithms are …
constraint violations in the evolutionary search process. Evolutionary algorithms are …
Memory backtracking strategy: An evolutionary updating mechanism for meta-heuristic algorithms
The search domain of meta-heuristic algorithms is always constantly changing, which make
it difficult to adapt the diverse optimization issues. To overcome above issue, an evolutionary …
it difficult to adapt the diverse optimization issues. To overcome above issue, an evolutionary …
A multi-strategy particle swarm algorithm with exponential noise and fitness-distance balance method for low-altitude penetration in secure space
UAV technology is at the forefront of current research and plays an important role in
agriculture, public safety and the military. Low altitude trajectory is a technology for UAVs to …
agriculture, public safety and the military. Low altitude trajectory is a technology for UAVs to …
Guided learning strategy: A novel update mechanism for metaheuristic algorithms design and improvement
H Jia, C Lu - Knowledge-Based Systems, 2024 - Elsevier
Meta-heuristic algorithms (MH) are naturally inspired global optimization algorithms. They
are often relatively simple and can solve problems in a short period of time, with certain …
are often relatively simple and can solve problems in a short period of time, with certain …
Improve coati optimization algorithm for solving constrained engineering optimization problems
The coati optimization algorithm (COA) is a meta-heuristic optimization algorithm proposed
in 2022. It creates mathematical models according to the habits and social behaviors of …
in 2022. It creates mathematical models according to the habits and social behaviors of …
Improved stochastic fractal search algorithm involving design operators for solving parameter extraction problems in real-world engineering optimization problems
The characteristic parameters of renewable energy sources (RESs) are changes over time
under changing operating conditions. Therefore, the accuracy of the model is important in …
under changing operating conditions. Therefore, the accuracy of the model is important in …
Validation of four optimization evolutionary algorithms combined with artificial neural network (ANN) for landslide susceptibility mapping: A case study of Gilan, Iran
H Moayedi, M Xu, P Naderian, AA Dehrashid… - Ecological …, 2024 - Elsevier
Landslides, the most significant geohazards in Iran, adversely affect the region's
socioeconomic conditions and the environment. Landslide susceptibility mapping is crucial …
socioeconomic conditions and the environment. Landslide susceptibility mapping is crucial …
PID-based search algorithm: a novel metaheuristic algorithm based on PID algorithm
Y Gao - Expert Systems With Applications, 2023 - Elsevier
In this paper, a metaheuristic algorithm called PID-based search algorithm (PSA) is
proposed for global optimization. The algorithm is based on an incremental PID algorithm …
proposed for global optimization. The algorithm is based on an incremental PID algorithm …
Love evolution algorithm: A stimulus–value–role theory-inspired evolutionary algorithm for global optimization
Y Gao, J Zhang, Y Wang, J Wang, L Qin - The Journal of Supercomputing, 2024 - Springer
This paper proposes the Love Evolution Algorithm (LEA), a novel evolutionary algorithm
inspired by the stimulus–value–role theory. The optimization process of the LEA includes …
inspired by the stimulus–value–role theory. The optimization process of the LEA includes …