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Pages in category "Nature-inspired metaheuristics" ... Spiral optimization algorithm; ... Bat algorithm; Bees algorithm; Biogeography-based optimization; C.
Seeker Optimization Algorithm SOA Nature-inspired Human-based 2006 [17] Imperialistic Competitive Algorithm ICA Nature-inspired Human-based 2007 [18] Central Force Optimization CFO 2007 [19] Biogeography Based Optimization BBO Nature-inspired Human-based 2008 [20] Firefly Algorithm FA Nature-inspired Bio-inspired 2008 [21] Intelligent Water ...
In the ant colony optimization algorithms, an artificial ant is a simple computational agent that searches for good solutions to a given optimization problem. To apply an ant colony algorithm, the optimization problem needs to be converted into the problem of finding the shortest path on a weighted graph. In the first step of each iteration ...
Lion algorithm (LA) is one among the bio-inspired (or) nature-inspired optimization algorithms (or) that are mainly based on meta-heuristic principles. It was first introduced by B. R. Rajakumar in 2012 in the name, Lion’s Algorithm.. [1] It was further extended in 2014 to solve the system identification problem. [2]
In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, tune, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem or a machine learning problem, especially with incomplete or imperfect information or limited computation capacity.
Evolutionary algorithms (EA), particle swarm optimization (PSO), differential evolution (DE), ant colony optimization (ACO) and their variants dominate the field of nature-inspired metaheuristics. [15] This list includes algorithms published up to circa the year 2000.
[24] [25] Moreover, a micro biogeography-inspired multi-objective optimization algorithm (μBiMO) was implemented: it is suitable for solving multi-objective optimisations in the field of industrial design because it is based on a small number of islands (hence the name μBiMO), i.e. few objective function calls are required. [26]
The runner-root algorithm (RRA) is a meta-heuristic optimization algorithm for solving unimodal and multimodal problems inspired by the runners and roots of plants in nature. Intelligent water drops algorithm (IWD) which mimics the behavior of natural water drops to solve optimization problems; Parallel tempering is a simulation of model copies ...