ScholarGate
Asszisztens

Módszerek összehasonlítása

Tekintse át a kiválasztott módszereket egymás mellett; az eltérő sorok kiemelve jelennek meg.

Tücsök algoritmus×Genetikus algoritmus×
TudományterületOptimalizálásOptimalizálás
MódszercsaládProcess / pipelineProcess / pipeline
Keletkezés éve20081975
MegalkotóXin-She YangJohn Henry Holland
TípusSwarm intelligence metaheuristicPopulation-based metaheuristic
AlapműYang, X.S. (2010). Firefly Algorithm, Stochastic Test Functions and Design Optimisation. International Journal of Bio-Inspired Computation, 2(2), 78-84. DOI ↗Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. link ↗
Alternatív nevekFA, Firefly Optimization, Ateşböceği Algoritması (Firefly Algorithm)GA, evolutionary algorithm, Genetik Algoritma — Evrimsel Optimizasyon
Kapcsolódó55
ÖsszefoglalóThe Firefly Algorithm (FA), introduced by Xin-She Yang in 2008 and formally published in 2010, is a nature-inspired swarm metaheuristic that models the bioluminescent attraction behaviour of fireflies. Each candidate solution is a firefly whose brightness represents its objective-function value; dimmer fireflies move toward brighter ones with an attraction force that decays with distance, driving the swarm toward optima without gradient information.A genetic algorithm (GA) is a population-based metaheuristic optimization method introduced by John Henry Holland (1975) that mimics the principles of natural selection. It maintains a population of candidate solutions and iteratively improves them through selection, crossover, and mutation operators, making it especially powerful on discontinuous, non-convex, and multi-modal search spaces where classical gradient-based methods fail.
ScholarGateAdatkészlet
  1. v1
  2. 2 Források
  3. PUBLISHED
  1. v1
  2. 2 Források
  3. PUBLISHED

Ugrás a kereséshez Download slides

ScholarGateMódszerek összehasonlítása: Firefly Algorithm · Genetic Algorithm. Letöltve 2026-06-15, forrás: https://scholargate.app/hu/compare