পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| ফায়ারফ্লাই অ্যালগরিদম× | পার্টিকেল সোয়ার্ম অপ্টিমাইজেশন (PSO)× | |
|---|---|---|
| ক্ষেত্র | অনুকূলকরণ | অনুকূলকরণ |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 2008 | 1995 |
| প্রবর্তক≠ | Xin-She Yang | — |
| ধরন≠ | Swarm intelligence metaheuristic | Population-based metaheuristic / swarm intelligence |
| মৌলিক উৎস≠ | Yang, X.S. (2010). Firefly Algorithm, Stochastic Test Functions and Design Optimisation. International Journal of Bio-Inspired Computation, 2(2), 78-84. DOI ↗ | Kennedy, J. & Eberhart, R. (1995). Particle Swarm Optimization. IEEE International Conference on Neural Networks (ICNN), 1942-1948. DOI ↗ |
| অপর নাম | FA, Firefly Optimization, Ateşböceği Algoritması (Firefly Algorithm) | PSO, swarm intelligence optimization, Parçacık Sürü Optimizasyonu (PSO) |
| সম্পর্কিত≠ | 5 | 6 |
| সারসংক্ষেপ≠ | 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. | Particle Swarm Optimization (PSO) is a population-based metaheuristic algorithm introduced by Kennedy and Eberhart in 1995, inspired by the collective movement of bird flocks and fish schools. Each candidate solution — called a particle — moves through the search space by updating its velocity and position based on its own best experience and the best experience of the entire swarm, enabling fast convergence across continuous optimization problems. |
| ScholarGateডেটাসেট ↗ |
|
|