ScholarGate
Asistent

Metaheuristike

48 metoda u ovoj obitelji.

Izdvojeno

Agent-based ant colony optimizationAgent-Based Ant Colony Optimization (AB-ACO) models individual ants as autonomous agents that probabilistically construct solutions by following and depositing pheromone trails on Agent-Based Genetic AlgorithmAn Agent-Based Genetic Algorithm (ABGA) partitions a genetic algorithm's population across a network of autonomous agents, each maintaining a local sub-population and evolving it iAgent-Based NSGA-IIAgent-based NSGA-II embeds the NSGA-II evolutionary algorithm inside an agent-based simulation loop so that objective values for each candidate solution are determined by running aAgent-Based Tabu SearchAgent-Based Tabu Search (ABTS) embeds the tabu search metaheuristic inside a multi-agent framework where autonomous agents each run independent or cooperating tabu search threads, Ant Colony OptimizationAnt Colony Optimization (ACO) is a metaheuristic algorithm introduced by Marco Dorigo and colleagues in the early 1990s that solves combinatorial optimisation problems by simulatinOptimizacija umjetnom kolonijom pčela (ABC)Artificial Bee Colony (ABC) is a population-based swarm intelligence metaheuristic introduced by Karaboga and Basturk in 2007. It models the cooperative foraging behavior of a hone

Put čitanja

Najreferentnije temeljne metode ove teme, poredane redoslijedom njihova razvoja — polazište ako ste ovdje novi.

  1. Genetički algoritam1975autor: John Henry Holland
  2. Simulirano žarenje1983
  3. Višeciljni genetički algoritam (MOGA)1984autor: Schaffer, J. D. (early MOGA); Goldberg, D. E. (GA foundations)
  4. Tabu Search1989autor: Fred Glover
  5. Ant Colony Optimization1992 (foundational thesis); 1997 (Ant Colony System formalization)
  6. Optimizacija rojem čestica (PSO)1995
  7. Diferencijalna evolucija1997autor: Rainer Storn & Kenneth Price
  8. Višeobjektna optimizacija rojem čestica (MOPSO)2004autor: Coello Coello, C. A., Pulido, G. T., & Lechuga, M. S.
sve metode na ovoj polici ↓

Sve metode 48

Agent-based ant colony optimizationAgent-Based Genetic AlgorithmAgent-Based NSGA-IIAgent-Based Tabu SearchAnt Colony OptimizationOptimizacija umjetnom kolonijom pčela (ABC)Algoritam šišmišaBayesian Ant Colony OptimizationBayesov genetski algoritamBayesian NSGA-IIBayesian Particle Swarm OptimizationBayesian Simulated AnnealingBayesovo tabu pretraživanjeMetaheuristika pretraživanja kukaviceDeterministički genetski algoritamDeterministička optimizacija rojem česticaDeterministički simulirani annealingDiferencijalna evolucijaAlgoritam krijesnicaGenetički algoritamOptimizator sivog vukaHarmony SearchHiperheuristikeMatheuristike: Hibridizacija matematičkog programiranja i metaheuristikaMemetički algoritamVišekriterijska optimizacija rojevima mrava (MOACO)Višeciljni genetički algoritam (MOGA)Višeobjektna optimizacija rojem čestica (MOPSO)Višeciljna simulirana kaljenost (MOSA)Višeciljano Tabu Pretraživanje (MOTS)NSGA-IINSGA-IIIOptimizacija rojem čestica (PSO)Genetski algoritam za analizu scenarija politikeOptimizacija roja čestica za scenarije politikaRobusna optimizacija kolonijom mravaRobusni genetski algoritamRobusni NSGA-IIRobusna optimizacija rojem česticaRobusno simulirano kaljenjeRobusno pretraživanje s tabu listomSimheuristicsSimulirano žarenjeStochastic Genetic AlgorithmStochastic NSGA-IIStochastic Particle Swarm OptimizationStochastic Tabu SearchTabu Search