The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The performance of the MAX -MIN ant system (MMAS) in dynamic optimization problems (DOPs) is sensitive to the colony size. In particular, a large colony size may waste computational resources whereas a small colony size may restrict the searching capabilities of the algorithm. There is a trade off in the behaviour of the algorithm between the early and later stages of the optimization process. A smaller colony size leads to better performance on shorter runs whereas a larger colony size leads to better performance on longer runs. In this paper, pre-scheduling of varying the colony size of MMAS is...
The approach of using multiple ant colonies is an extension of the Ant Colony Optimization framework...
In ant colony optimization (ACO) methods, including Ant System and MAX-MIN Ant System, each ant stoc...
Ant colony optimization (ACO) performs very well on many hard optimization problems, even though no ...
The file attached to this record is the author's final peer reviewed version.In this paper, the effe...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
Ant colony optimization is a swarm intelligence metaheuristic inspired by the foraging behavior of s...
The ant colony optimization (ACO) metaheuristic is inspired by the foraging behaviour of real ant co...
The ant colony optimization (ACO) metaheuristic was inspired from the foraging behaviour of real ant...
Ant colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization pro...
In ant colony optimization (ACO) methods, including Ant System and MAX-MIN Ant System, each ant stoc...
Ant System, the first Ant Colony Optimization algorithm, showed to be a viable method for attacking ...
A multi-colony ant colony optimization (ACO) algorithm consists of several colonies of ants. Each co...
A comparison of six basic Ant Colony Optimization (ACO) in dynamic environment was studied in this p...
Abstract: Ant Colony Optimization (ACO) has been commonly applied in solving discrete optimization p...
Ant colony optimization (ACO) algorithms are computational problem-solving methods that are inspired...
The approach of using multiple ant colonies is an extension of the Ant Colony Optimization framework...
In ant colony optimization (ACO) methods, including Ant System and MAX-MIN Ant System, each ant stoc...
Ant colony optimization (ACO) performs very well on many hard optimization problems, even though no ...
The file attached to this record is the author's final peer reviewed version.In this paper, the effe...
The file attached to this record is the author's final peer reviewed version. The Publisher's final ...
Ant colony optimization is a swarm intelligence metaheuristic inspired by the foraging behavior of s...
The ant colony optimization (ACO) metaheuristic is inspired by the foraging behaviour of real ant co...
The ant colony optimization (ACO) metaheuristic was inspired from the foraging behaviour of real ant...
Ant colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization pro...
In ant colony optimization (ACO) methods, including Ant System and MAX-MIN Ant System, each ant stoc...
Ant System, the first Ant Colony Optimization algorithm, showed to be a viable method for attacking ...
A multi-colony ant colony optimization (ACO) algorithm consists of several colonies of ants. Each co...
A comparison of six basic Ant Colony Optimization (ACO) in dynamic environment was studied in this p...
Abstract: Ant Colony Optimization (ACO) has been commonly applied in solving discrete optimization p...
Ant colony optimization (ACO) algorithms are computational problem-solving methods that are inspired...
The approach of using multiple ant colonies is an extension of the Ant Colony Optimization framework...
In ant colony optimization (ACO) methods, including Ant System and MAX-MIN Ant System, each ant stoc...
Ant colony optimization (ACO) performs very well on many hard optimization problems, even though no ...