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 …

Abstract The Bees Algorithm models the foraging behaviour of honeybees in order to solve
optimization problems. The algorithm performs a kind of exploitative neighbourhood search …

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 …

This paper presents glowworm swarm optimization (GSO), a novel algorithm for the
simultaneous computation of multiple optima of multimodal functions. The algorithm shares …

A novel optimization algorithm is presented, inspired by group hunting of animals such as
lions, wolves, and dolphins. Although these hunters have differences in the way of hunting …

This paper presents an exposition of a new method of swarm intelligence based algorithm
for optimising multi-modal functions. The main objective of using this method is to ensure …

This paper proposes PSACO (particle swarm ant colony optimization) algorithm for highly
non-convex optimization problems. Both particle swarm optimization (PSO) and ant colony …

Blasting is the process of use of explosives to excavate or remove the rock mass. The main
objective of blasting operation is to provide proper rock fragmentation and to avoid …

This paper presents multimodal function optimization, using a nature-inspired glowworm
swarm optimization (GSO) algorithm, with applications to collective robotics. GSO is similar …

In this article, we propose UACOR, a unified ant colony optimization (ACO) algorithm for
continuous optimization. UACOR includes algorithmic components from ACO R, DACO R …