Abstract Ant Colony Optimization (ACO) is a metaheuristic that is inspired by the pheromone
trail laying and following behavior of some ant species. Artificial ants in ACO are stochastic …

Ant colony optimization is a technique for optimization that was introduced in the early
1990's. The inspiring source of ant colony optimization is the foraging behavior of real ant …

Abstract Peer-to-Peer (P2P) energy trading, which allows energy consumers/producers to
directly trade with each other, is one of the new paradigms driven by the decarbonization …

This paper proposes a new path planning approach for emergency evacuation simulation.
This technique combines the Extended Social Force Model (ESFM) and the Improved …

A unified view of metaheuristics This book provides a complete background on
metaheuristics and shows readers how to design and implement efficient algorithms to solve …

The ant colony optimization (ACO) is one efficient approach for solving the travelling
salesman problem (TSP). Here, we propose a hybrid algorithm based on state-adaptive …

Swarm intelligence is a relatively new approach to problem solving that takes inspiration
from the social behaviors of insects and of other animals. In particular, ants have inspired a …

Research on a new metaheuristic for optimization is often initially focused on proof-of-
concept applications. It is only after experimental work has shown the practical interest of the …

Metaheuristics are general algorithmic frameworks, often nature-inspired, designed to solve
complex optimization problems, and they are a growing research area since a few decades …

Conclusions The field of ACO algorithms is very lively, as testified, for example, by the
successful biannual workshop (ANTS—From Ant Colonies to Artificial Ants: A Series of …