In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems that can be reduced to finding good paths through graphs. Artificial ants represent multi …

2020年5月17日 · Ant Colony Optimization technique is purely inspired from the foraging behaviour of ant colonies, first introduced by Marco Dorigo in the 1990s. Ants are eusocial insects that prefer community survival and sustaining rather than as individual species.

2005年12月1日 · The inspiring source of ant colony optimization is the foraging behavior of real ant colonies. This behavior is exploited in artificial ant colonies for the search of approximate solutions to discrete optimization problems, to continuous optimization problems, and to important problems in telecommunications, such as routing and load balancing.

2021年6月24日 · In this paper, we develop and implement a Bayesian simulation model derived from the active inference framework that captures some of the underlying dynamics and emergent phenomena of ant colony foraging behavior. In our model, we focus on the stigmergic outcomes of foragers using a single trail pheromone molecule. Assuming that each agent ...

2024年7月1日 · This study proposed a historical-information-based patch-level multi-type ant colony optimization (HI-PMACO) model to examine the effect of incorporating historical information into the optimization model from both macro and local perspectives.

Ant colony optimization (ACO) takes inspiration from the foraging behavior of some ant species. These ants deposit pheromone on the ground in order to mark some favorable path that should be followed by other members of the colony. Ant colony optimization exploits a similar mechanism for solv-ing optimization problems. From the early nineties ...

2024年2月16日 · The purpose of this chapter is to present a comprehensive grasp of ant colony optimization (ACO) algorithms and how they are used to advance intelligent systems. It provides information on how ant colony optimization methods work and how many different engineering...

Many special cases of the ACO metaheuristic have been proposed. The three most successful ones are: Ant System, Ant Colony System (ACS), and MAX-MIN Ant System (MMAS). For illustration, example problem used is Travelling Salesman Problem.

2025年2月21日 · Global path planning remains a critical challenge in mobile robots, with ant colony optimization (ACO) being widely adopted for its swarm intelligence characteristics. To address the inherent limitations of ACO, this study proposes an intelligently enhanced ACO (IEACO) incorporating six innovative strategies. First, the early search efficiency is improved by implementing a non-uniform initial ...

5 天之前 · This paper proposes a spatiotemporal model of land use change based on ant colony optimization (ACO), Markov chain and cellular automata (CA). These three methodologies have previously been used separately or in pairs to simulate land use change. In this paper, we apply them in combination, using ant colony optimization and cellular automata to ...