Ant-colony optimization algorithm is an evolutionary learning algorithm which could be applied to solve the complex problems.

Scientists found that ants and other natural systems use optimization algorithms similar to those used by engineered systems, including the Internet.

Abstract: Ant colony optimization (ACO) is one of the most famous bio-inspired algorithms. Its theoretical research contains convergence proof and runtime analysis. The convergence of ACO has been ...

ABSTRACT Growing concerns about the environment, energy dependency, and the unstable fuel prices have increased the sales of electric vehicles. Energy-efficient routing for electric vehicles requires ...

Optimization 3: Combining/Balancing MPI Ranks and OpenMP Threads Summary Background: The ACO Algorithm When ants search for food, they deposit pheromones along their paths, which attract more ants.

Gordon has found parallels between the algorithms ant colonies use for foraging and the man-made ones that underlie the Internet.

It has driven the research towards exploring different methodologies like meta-heuristic algorithms for enhancing big data clustering performance. One promising meta-heuristic approach is Ant-Bee ...