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 …

Following decades of sustained improvement, metaheuristics are one of the great success
stories of optimization research. However, in order for research in metaheuristics to avoid …

Research in metaheuristics for combinatorial optimization problems has lately experienced
a noteworthy shift towards the hybridization of metaheuristics with other techniques for …

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 …

This paper is intended to give a review of metaheuristic and their application to
combinatorial optimization problems. This paper comprises a snapshot of the rapid evolution …

Balancing bike sharing systems is an increasingly important problem, because of the rising
popularity of this mean of transportation. Bike sharing systems need to be balanced so that …

The ability of ant colonies to form paths for carrying food is rather fascinating. When
considering the scale of ants, this path-finding problem is complex: ants only have a local …

The combination of components from different algorithms is currently one of the most
successful trends in optimization. The hybridization of metaheuristics such as ant colony …

Ant Colony Optimization (ACO)[1, 2, 3] is a metaheuristic for solving hard combinatorial
optimization problems inspired by the indirect communication of real ants. In ACO …

This paper describes and evaluates approaches to model and solve technical product
configuration problems using different artificial intelligence methodologies. By means of a …