General-purpose search methods that borrow ideas from nature or physics to find good solutions, such as particle swarm optimization, ant colony optimization, tabu search, differential evolution, the firefly algorithm and the artificial bee colony algorithm. An algorithm belongs here when its cited article calls it a metaheuristic or a nature-inspired optimization algorithm. It excludes exact linear programming methods.
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Metaheuristic Optimization Algorithms
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Wikipedia: Particle swarm optimization
Has Member: Particle Swarm Optimization Algorithm, Lead sectionQuote, Has Member: Particle Swarm Optimization Algorithm, Lead section
is a computational method that optimizes a problem
Wikipedia: Ant colony optimization algorithms
Has Member: Ant Colony Optimization Algorithm, Lead sectionQuote, Has Member: Ant Colony Optimization Algorithm, Lead section
is a probabilistic technique for solving computational problems
Wikipedia: Tabu search
Has Member: Tabu Search Algorithm, Lead sectionQuote, Has Member: Tabu Search Algorithm, Lead section
is a metaheuristic search method
Differential Evolution (Wikipedia)
Has Member: Differential Evolution, Lead sectionQuote, Has Member: Differential Evolution, Lead section
is an evolutionary algorithm to optimize a problem
Firefly algorithm (Wikipedia)
Has Member: Firefly Algorithm, Lead sectionQuote, Has Member: Firefly Algorithm, Lead section
is a metaheuristic proposed by Xin-She Yang
Bat Algorithm (Wikipedia)
Has Member: Bat Algorithm, Lead sectionQuote, Has Member: Bat Algorithm, Lead section
is a metaheuristic algorithm for global optimization
Artificial Bee Colony Algorithm (Wikipedia)
Has Member: Artificial Bee Colony Algorithm, Lead sectionQuote, Has Member: Artificial Bee Colony Algorithm, Lead section
is an optimization algorithm based on the intelligent foraging
Variable Neighborhood Search (Wikipedia)
Has Member: Variable Neighborhood Search, Lead sectionQuote, Has Member: Variable Neighborhood Search, Lead section
is a metaheuristic method for solving a set of combinatorial optimization
Greedy Randomized Adaptive Search Procedure (Wikipedia)
Has Member: Greedy Randomized Adaptive Search Procedure, Lead sectionQuote, Has Member: Greedy Randomized Adaptive Search Procedure, Lead section
is a metaheuristic algorithm commonly applied to combinatorial optimization
Wikipedia: Hill Climbing Algorithm
Wikimedia FoundationHas Member: Hill Climbing Algorithm, LeadQuote, Has Member: Hill Climbing Algorithm, Lead
In numerical analysis, hill climbing is a mathematical optimization technique which belongs to the family of local search.
CMA-ES (Wikipedia)
Has Member: CMA-ES, LeadQuote, Has Member: CMA-ES, Lead
Covariance matrix adaptation evolution strategy (CMA-ES) is a particular kind of strategy for numerical optimization.
Wikipedia: Simulated annealing
Wikimedia FoundationHas Member: Simulated Annealing Algorithm, LeadQuote, Has Member: Simulated Annealing Algorithm, Lead
Simulated annealing (SA) is a probabilistic technique for approximating the global optimum of a given function.
Lion (Wikipedia)
Has Member: Lion Algorithm, LeadQuote, Has Member: Lion Algorithm, Lead
Lion algorithm (LA) is one among the bio-inspired (or) nature-inspired optimization algorithms (or) that are mainly based on meta-heuristic principles.
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