পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| এজেন্ট-ভিত্তিক জেনেটিক অ্যালগরিদম× | পার্টিকেল সোয়ার্ম অপ্টিমাইজেশন (PSO)× | |
|---|---|---|
| ক্ষেত্র≠ | অনুকরণ | অনুকূলকরণ |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 1990s | 1995 |
| প্রবর্তক≠ | Adamidis, P. & Petridis, V. (early formal treatment); broader community development in 1990s | — |
| ধরন≠ | Hybrid evolutionary-agent simulation | Population-based metaheuristic / swarm intelligence |
| মৌলিক উৎস≠ | Adamidis, P., & Petridis, V. (1996). Co-operating populations with different evolution behaviors. Proceedings of the IEEE International Conference on Evolutionary Computation (ICEC 1996), 188-191. IEEE. link ↗ | Kennedy, J. & Eberhart, R. (1995). Particle Swarm Optimization. IEEE International Conference on Neural Networks (ICNN), 1942-1948. DOI ↗ |
| অপর নাম≠ | ABGA, Agent-Based GA, Multi-Agent Genetic Algorithm, Distributed Agent GA | PSO, swarm intelligence optimization, Parçacık Sürü Optimizasyonu (PSO) |
| সম্পর্কিত≠ | 5 | 6 |
| সারসংক্ষেপ≠ | An 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 independently. Agents periodically exchange individuals (migration) based on proximity or communication rules, enabling parallel exploration of the search space while preserving population diversity and avoiding premature convergence. | 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 ↗ |
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