Recent advances in differential evolution–an updated survey
Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary
optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed …
optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed …
Differential evolution and its applications in image processing problems: a comprehensive review
Differential evolution (DE) is one of the highly acknowledged population-based optimization
algorithms due to its simplicity, user-friendliness, resilience, and capacity to solve problems …
algorithms due to its simplicity, user-friendliness, resilience, and capacity to solve problems …
A survey on evolutionary computation for complex continuous optimization
Complex continuous optimization problems widely exist nowadays due to the fast
development of the economy and society. Moreover, the technologies like Internet of things …
development of the economy and society. Moreover, the technologies like Internet of things …
A two-stage cooperative evolutionary algorithm with problem-specific knowledge for energy-efficient scheduling of no-wait flow-shop problem
Green scheduling in the manufacturing industry has attracted increasing attention in
academic research and industrial applications with a focus on energy saving. As a typical …
academic research and industrial applications with a focus on energy saving. As a typical …
SCA: a sine cosine algorithm for solving optimization problems
S Mirjalili - Knowledge-based systems, 2016 - Elsevier
This paper proposes a novel population-based optimization algorithm called Sine Cosine
Algorithm (SCA) for solving optimization problems. The SCA creates multiple initial random …
Algorithm (SCA) for solving optimization problems. The SCA creates multiple initial random …
A constrained differential evolution algorithm to solve UAV path planning in disaster scenarios
X Yu, C Li, JF Zhou - Knowledge-Based Systems, 2020 - Elsevier
Disasters have caused significant losses to humans in the past decades. It is essential to
learn about the disaster situation so that rescue works can be conducted as soon as …
learn about the disaster situation so that rescue works can be conducted as soon as …
A dual-population-based evolutionary algorithm for constrained multiobjective optimization
The main challenge in constrained multiobjective optimization problems (CMOPs) is to
appropriately balance convergence, diversity and feasibility. Their imbalance can easily …
appropriately balance convergence, diversity and feasibility. Their imbalance can easily …
Hybrid evolutionary-based sparse channel estimation for IRS-assisted mmWave MIMO systems
The intelligent reflecting surface (IRS)-assisted millimeter wave (mmWave) communication
system has emerged as a promising technology for coverage extension and capacity …
system has emerged as a promising technology for coverage extension and capacity …
Search and rescue optimization algorithm: A new optimization method for solving constrained engineering optimization problems
A new optimization method namely the Search and Rescue optimization algorithm (SAR) is
presented here to solve constrained engineering optimization problems. This metaheuristic …
presented here to solve constrained engineering optimization problems. This metaheuristic …
Mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems
A novel population-based algorithm based on the mine bomb explosion concept, called the
mine blast algorithm (MBA), is applied to the constrained optimization and engineering …
mine blast algorithm (MBA), is applied to the constrained optimization and engineering …