Optimization is an art that is best performed by a well-tuned algorithm. Nature - instead of being fully deterministic - is evolutionary, vibrant and resourceful. The nature-inspired algorithms use the best combination and evolution strategy in a given situation. In this work, a new metaheuristic...
In this study, a novel metaheuristic optimization algorithm, gradient-based optimizer (GBO) is proposed. The GBO, inspired by the gradient-based Newton's method, uses two main operators: gradient search rule (GSR) and local escaping operator (LEO) and a set of vectors to explore the search ...
In this study, a new metaheuristic optimization algorithm, called cuckoo search (CS), is introduced for solving structural optimization tasks. The new CS algorithm in combination with Lévy flights is first verified using a benchmark nonlinear constrained optimization problem. For the validation against...
plants, insects, and other organisms to develop powerful optimization methods. Particle swarm optimization (PSO)34, ant colony optimization (ACO)35, artificial bee colony (ABC)36, and firefly algorithm (FA)37are among the most widely recognized swarm-based metaheuristic algorithms. ...
Therefore, researchers have developed many metaheuristic algorithms and successfully applied them to the solution of optimization problems. Among them, Particle swarm optimization (PSO) algorithm6 is one of the most widely used swarm intelligence algorithms. However, the basic PSO has a simple operating...
This paper proposes a novel robust power system stabilizer (PSS), based on hybridization of fractional order PID controller (PIλDμ) and PSS for optimal stabilizer (FOPID-PSS) for the first time, using a new metaheuristic optimization Bat algorithm (BA) inspired by the echolocation behavior to...
(2020). Gradient-based optimizer: A new metaheuristic optimization algorithm. Information Sciences, 540, 131-159. H HC - Hill Climbing . OriginalHC: Talbi, E. G., & Muntean, T. (1993, January). Hill-climbing, simulated annealing and genetic algorithms: a comparative study and application ...
A new metaheuristic bat-inspired algorithm, nature inspired cooperative strategies for optimization (NISCO 2010) X. S. Yang, "A new metaheuristic bat-inspired algorithm. Nature Inspired Cooperative Strategies for Optimization (NICSO)," Studies in Computational ... Y Xin-She 被引量: 125发表: 2010...
This work proposes a different algorithm inspired by African vulture's lifestyles with a comprehensive model to develop a new metaheuristic optimization algorithm. Some of the contributions of this paper are as follows: In the remainder of the paper, Section 2 deals with nature-inspired metaheuristic...
This paper proposes using the metaheuristic model EOSA-CNN for breast cancer detection using gene expression data34. EOSA is a new optimization algorithm with excellent performance track records in different application domains35,36,37,38,39. It is population-based and bio-inspired, developed by ...