Krahasoni metodat

	Optimizimi me bazë agjentësh i Kolonisë së Miarave	Optimizimi me Antet
Fusha	Simulimi	Optimizimi
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	1992-2004	1992 (foundational thesis); 1997 (Ant Colony System formalization)
Krijuesi	Dorigo, M. and colleagues; agent-based framing developed in swarm intelligence community	—
Lloji	Metaheuristic optimization — agent-based swarm simulation	Metaheuristic — swarm intelligence
Burimi themelues	Dorigo, M., Stutzle, T. (2004). Ant Colony Optimization. MIT Press, Cambridge, MA. ISBN: 9780262042192	Dorigo, M. & Gambardella, L.M. (1997). Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Transactions on Evolutionary Computation, 1(1), 53-66.
Emërtime të tjera	AB-ACO, Agent-Based ACO, Multi-Agent Ant Colony Optimization, MAACO	ACO, Karınca Kolonisi Optimizasyonu (ACO), ant colony system
Të lidhura	5	5
Përmbledhja	Agent-Based Ant Colony Optimization (AB-ACO) models individual ants as autonomous agents that probabilistically construct solutions by following and depositing pheromone trails on a search graph. By coupling agent-level behavioral rules with a shared pheromone environment, the collective system converges on high-quality solutions to hard combinatorial and simulation-embedded optimization problems without central coordination.	Ant Colony Optimization (ACO) is a metaheuristic algorithm introduced by Marco Dorigo and colleagues in the early 1990s that solves combinatorial optimisation problems by simulating the collective foraging behaviour of ants. Real ants lay pheromone trails on paths and preferentially follow stronger trails; ACO turns this positive-feedback mechanism into a search procedure that finds high-quality solutions to graph-structured problems such as the Travelling Salesman Problem, vehicle routing, and scheduling.