A review of population-based metaheuristics for large-scale black-box global optimization—Part I
Scalability of optimization algorithms is a major challenge in co** with the ever-growing
size of optimization problems in a wide range of application areas from high-dimensional …
size of optimization problems in a wide range of application areas from high-dimensional …
A review on constraint handling techniques for population-based algorithms: from single-objective to multi-objective optimization
Most real-world problems involve some type of optimization problems that are often
constrained. Numerous researchers have investigated several techniques to deal with …
constrained. Numerous researchers have investigated several techniques to deal with …
A survey on evolutionary constrained multiobjective optimization
Handling constrained multiobjective optimization problems (CMOPs) is extremely
challenging, since multiple conflicting objectives subject to various constraints require to be …
challenging, since multiple conflicting objectives subject to various constraints require to be …
A social learning particle swarm optimization algorithm for scalable optimization
Social learning plays an important role in behavior learning among social animals. In
contrast to individual (asocial) learning, social learning has the advantage of allowing …
contrast to individual (asocial) learning, social learning has the advantage of allowing …
Cloud-assisted secure eHealth systems for tamper-proofing EHR via blockchain
The wide deployment of cloud-assisted electronic health (eHealth) systems has already
shown great benefits in managing electronic health records (EHRs) for both medical …
shown great benefits in managing electronic health records (EHRs) for both medical …
An evolutionary gravitational search-based feature selection
With recent advancements in data collection tools and the widespread use of intelligent
information systems, a huge amount of data streams with lots of redundant, irrelevant, and …
information systems, a huge amount of data streams with lots of redundant, irrelevant, and …
A survey of advances in landscape analysis for optimisation
KM Malan - Algorithms, 2021 - mdpi.com
Fitness landscapes were proposed in 1932 as an abstract notion for understanding
biological evolution and were later used to explain evolutionary algorithm behaviour. The …
biological evolution and were later used to explain evolutionary algorithm behaviour. The …
A hybrid GSA-GA algorithm for constrained optimization problems
H Garg - Information Sciences, 2019 - Elsevier
In this paper, a new hybrid GSA-GA algorithm is presented for the constraint nonlinear
optimization problems with mixed variables. In it, firstly the solution of the algorithm is tuned …
optimization problems with mixed variables. In it, firstly the solution of the algorithm is tuned …
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 …
Applications of new hybrid algorithm based on advanced cuckoo search and adaptive Gaussian quantum behaved particle swarm optimization in solving ordinary …
This article solves first and second order differential equations with initial and/or boundary
conditions by transforming these equations into unconstrained/bound constrained …
conditions by transforming these equations into unconstrained/bound constrained …