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Firefly Algorithm
Metaheuristic optimization algorithm inspired by the flashing behavior of fireflies to find optimal solutions in complex search spaces.
Light intensity
Measure of a firefly's attractiveness, directly proportional to the quality of its solution and used to guide the movement of other individuals.
Attraction distance
Euclidean distance or other metric calculated between two fireflies to determine mutual influence and the probability of attraction.
Light absorption coefficient
Gamma parameter controlling the decrease in light intensity with distance, modulating the range of attraction between fireflies.
Randomization factor
Alpha parameter introducing a stochastic component in the movement of fireflies to avoid local optima and promote exploration.
Firefly movement
Position update equation combining attraction towards brighter fireflies and random movement to explore the solution space.
Search space
Multidimensional domain containing all possible solutions to the optimization problem explored by the firefly algorithm.
Algorithm convergence
Process by which fireflies gradually converge towards optimal regions of the search space, forming clusters.
Exploration vs exploitation
Dynamic balance between discovering new regions of the search space and exploiting already identified promising solutions.
Firefly population
Set of simulated agents representing candidate solutions, whose collective evolution guides the search for optimum.
Multi-objective Firefly Algorithm
Extension of the base algorithm to simultaneously handle multiple conflicting objective functions in optimization problems.
Parametric adaptability
Mechanism dynamically adjusting the alpha, beta and gamma parameters during execution to improve convergence performance.