Metaheuristics

Machine Learning

Fuzzy Systems

Applications

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Day: September 6, 2015

Metaheuristics

Firefly Algorithm (FA) in MATLAB

Firefly Algorithm (FA) is a metaheuristic algorithm for global optimization, which is inspired by flashing behavior of firefly insects. This algorithm is proposed by

Machine Learning

DBSCAN Clustering in MATLAB

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a density-based clustering algorithm, proposed by Martin Ester et al., 1996. The algorithm finds neighbors

Metaheuristics

Invasive Weed Optimization (IWO) in MATLAB

Invasive Weed Optimization (IWO) is a nature-inspired metaheuristic, inspired by spreading strategy of weeds, and proposed by Alireza Mehrabian and Caro Lucas, in 2006.

Metaheuristics

Imperialist Competitive Algorithm (ICA) in MATLAB

Imperialist Competitive Algorithm (ICA), also known as Colonial Competitive Algorithm (CCA), is a sociopolitical metaheuristics, inspired by historical colonization process and competition among imperialists,

Metaheuristics

Tabu Search (TS) in MATLAB

Tabu Search (TS) is a local search-based metaheuristic, which is proposed by Fred W. Glover, in 1986. Tabu Search is completely based on the

Metaheuristics

Biogeography-Based Optimization (BBO) in MATLAB

Biogeography-Based Optimization (BBO) is an evolutionary algorithm and metaheuristic, which is inspired by the biogeographic concepts: speciation (the evolution of new species), the migration

Metaheuristics

CMA-ES in MATLAB

Evolution Strategy (ES) is the first and oldest evolutionary algorithm, and it is based on the adaptation and evolution. Specially, the main concept used

Metaheuristics

Differential Evolution (DE) in MATLAB

Differential Evolution (DE) is an evolutionary algorithm, which uses the difference of solution vectors to create new candidate solutions. The key points, in the

Metaheuristics

Simulated Annealing in MATLAB

Simulated Annealing (SA) is a metaheuristic, inspired by annealing process. SA starts with an initial solution at higher temperature, where the changes are accepted