The application of advanced analytics in science and technology is rapidly expanding, and developing optimization technics is critical to this expansion. Instead of relying on dated procedures, researchers can reap greater rewards by utilizing cutting-edge optimization techniques like population-based metaheuristic models, which can quickly generate a solution with acceptable quality. Ant Colony Optimization (ACO) is one the most critical and widely used models among heuristics and meta-heuristics. This book discusses ACO applications in Hybrid Electric Vehicles (HEVs), multi-robot systems, wireless multi-hop networks, and preventive, predictive maintenance
Abstract:- Over the last decade, evolutionary and meta-heuristic algorithms have been extensively us...
"Theoretical Computer Science Top Cited Article 2005-2010"Research on a new metaheuristic for optimi...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
Ant Colony Optimization (ACO) is the best example of how studies aimed at understanding and modeling...
. Ant Colony Optimization (ACO) is a class of constructive metaheuristic algorithms sharing the comm...
Ant colony optimization is a swarm intelligence metaheuristic inspired by the foraging behavior of s...
Ant Colony Optimization (ACO) is a class of constructive metaheuristic algorithms sharing the common...
Combinatorial optimization problems are of high academical as well as practical importance. Many ins...
AbstractResearch on a new metaheuristic for optimization is often initially focused on proof-of-conc...
Optimisation, in the mathematical sense, is the process of finding solutions to a problem such that ...
Ant Colony Optimization (ACO) [31, 32] is a recently proposed metaheuristic ap-proach for solving ha...
Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the s...
The purpose of this book is to provide a comprehensive overview of the current state of the art in a...
Colony Optimization (ACO) is a metaheuristic that inspired by the behaviour of real ant colonies and...
Optimizacija kolonijom mrava (ACO) je metaheuristika koja se uspješno primjenjuje za rješavanje tešk...
Abstract:- Over the last decade, evolutionary and meta-heuristic algorithms have been extensively us...
"Theoretical Computer Science Top Cited Article 2005-2010"Research on a new metaheuristic for optimi...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
Ant Colony Optimization (ACO) is the best example of how studies aimed at understanding and modeling...
. Ant Colony Optimization (ACO) is a class of constructive metaheuristic algorithms sharing the comm...
Ant colony optimization is a swarm intelligence metaheuristic inspired by the foraging behavior of s...
Ant Colony Optimization (ACO) is a class of constructive metaheuristic algorithms sharing the common...
Combinatorial optimization problems are of high academical as well as practical importance. Many ins...
AbstractResearch on a new metaheuristic for optimization is often initially focused on proof-of-conc...
Optimisation, in the mathematical sense, is the process of finding solutions to a problem such that ...
Ant Colony Optimization (ACO) [31, 32] is a recently proposed metaheuristic ap-proach for solving ha...
Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the s...
The purpose of this book is to provide a comprehensive overview of the current state of the art in a...
Colony Optimization (ACO) is a metaheuristic that inspired by the behaviour of real ant colonies and...
Optimizacija kolonijom mrava (ACO) je metaheuristika koja se uspješno primjenjuje za rješavanje tešk...
Abstract:- Over the last decade, evolutionary and meta-heuristic algorithms have been extensively us...
"Theoretical Computer Science Top Cited Article 2005-2010"Research on a new metaheuristic for optimi...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...