During the past few years, research in applying machine learning (ML) to design efficient,
effective, and robust metaheuristics has become increasingly popular. Many of those …

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 …

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 …

The paper presents an efficient Hybrid Genetic Search with Advanced Diversity Control for a
large class of time-constrained vehicle routing problems, introducing several new features to …

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 …

The Vehicle Routing Problem (VRP) was introduced 50 years ago by Dantzig and Ramser
under the title “The Truck Dispatching Problem.” The study of the VRP has given rise to …

We present a unified heuristic which is able to solve five different variants of the vehicle
routing problem: the vehicle routing problem with time windows (VRPTW), the capacitated …

The attributes of vehicle routing problems are additional characteristics or constraints that
aim to better take into account the specificities of real applications. The variants thus formed …

In this paper we present an extension of ant colony optimization (ACO) to continuous
domains. We show how ACO, which was initially developed to be a metaheuristic for …

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 …