เปรียบเทียบวิธี

	Bat Algorithm	Firefly Algorithm
สาขาวิชา	การหาค่าเหมาะที่สุด	การหาค่าเหมาะที่สุด
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	2010	2008
ผู้ริเริ่ม	Xin-She Yang	Xin-She Yang
ประเภท	Population-based swarm intelligence	Swarm intelligence metaheuristic
แหล่งต้นตำรับ	Yang, X.-S. (2010). A new metaheuristic bat-inspired algorithm. Nature Inspired Cooperative Strategies for Optimization (NICSO), 65–74.	Yang, X.S. (2010). Firefly Algorithm, Stochastic Test Functions and Design Optimisation. International Journal of Bio-Inspired Computation, 2(2), 78-84.
ชื่อเรียกอื่น	BA, Bat-Inspired Algorithm, Echolocation-Based Optimization, Yarasa Algoritması	FA, Firefly Optimization, Ateşböceği Algoritması (Firefly Algorithm)
ที่เกี่ยวข้อง	3	5
สรุป	The Bat Algorithm (BA) is a nature-inspired metaheuristic optimization method proposed by Xin-She Yang in 2010. It mimics the echolocation behavior of microbats to balance global exploration and local exploitation. Each artificial bat adjusts its position, velocity, and emission frequency, with loudness and pulse rate dynamically controlling the transition from broad search to refined local tuning. BA is suited to continuous and combinatorial optimization problems across engineering, scheduling, and machine learning domains.	The 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.