Ant colony optimization is a well known metaheuristic which has been object of many studies, both theoretic and applicative. In a recent analysis [1], a particular aspect of its behavior is investigated. More in detail, the topic object of interest is the result achieved by ant algorithms when the cost unit in which instances are expressed changes. Three ant colony optimization algorithms are p...

Cloud Computing is growing rapidly and clients are demanding more services with better results. Therefore, load balancing as well as task scheduling in the Cloud has become a very interesting and important research area. In this paper, we present proposed approach for improving parameters in ant colonies function. The suggested definition of a new computational paradigm, is called Ant Colony Op...

Recently, various sophisticated strategies adapted to current network conditions have been proposed for channel allocation based on intelligent techniques such as evolutionary and genetic algorithms. These approaches constitute heuristic solutions to resource management problems in modern cellular systems. On the other hand, the ant colony optimization approach has been proposed for solving sev...

Stochastic solvers are researched primarily with the goal of providing ‘black box’ optimisation approaches for situations where the optimisation problem is too complex to model and therefore impossible to solve using a deterministic approach. Sometimes, however, problems or their instances have characteristics which interact with the solver in undocumented and unpredictable ways. This paper rev...

Stochastic solvers are researched primarily with the goal of providing ‘black box’ optimisation approaches for situations where the optimisation problem is too complex to model and therefore impossible to solve using a deterministic approach. Sometimes, however, problems or their instances have characteristics which interact with the solver in undocumented and unpredictable ways. This paper rev...