Many scientific applications running in Cloud Computing system are workflow applications that contains large number of tasks and in which tasks are connected by precedence relations. Efficient scheduling the workflow tasks become a challenging issue in Cloud Computing environments because the scheduling decides performance of the applications. Unfortunately, finding the optimal scheduling is kn...

Ant Colony Optimization (ACO) is a new population oriented search metaphor that has been successfully applied toNP-hard combinatorial optimization problems. In this paper we discuss parallelization strategies for Ant Colony Optimization algorithms. We empirically test the most simple strategy, that of executing parallel independent runs of an algorithm. The empirical tests are performed applyin...

Quadratic assignment problem (QAP) is one of fundamental combinatorial optimization problems in many fields. Many real world applications such as backboard wiring, typewriter keyboard design and scheduling can be formulated as QAPs. Ant colony algorithm is a multi-agent system inspired by behaviors of real ant colonies to solve optimization problems. Ant colony optimization (ACO) is one of new ...

There has been an explosion of cloud services as organizations take advantage their continuity, predictability, well quality service and it raises the concern about latency, energy-efficiency, security. This increase in demand requires new configurations networks, products, operators. For this purpose, software-defined network is efficient technology that enables to support future functions alo...

-In this article two different optimization algorithms are presented to solve the deficiency of ant colony algorithm such as slow convergence rate and easy to fall into local optimum. This method based on Max-Min Ant System, established an adaptive model for pheromone evaporation coefficient adjusted adaptively and avoided the ants falling into local optimum. At the same time, this optimization...

An Ants System is an artificial system based on the behavior of real ant colonies, which is used to solve combinatorial problems. This is a distributed algorithm composed by a set of cooperating agents called ants which cooperate among them to find good solutions to combinatorial optimization problems. The cooperation follows the behavior of real ants using an indirect form of communication med...

In this paper is presented a distributed algorithm based on Ant System concepts, called Combinatorial Ant System, to solve dynamic combinatorial optimization problems. Our approach consists of mapping the solution space of the dynamic combinatorial optimization problem in the space where the ants will walk, and defining the transition probability and the pheromone update formula of the Ant Syst...

This paper addresses the optimal power flow problem in direct current (DC) networks employing a master–slave solution methodology that combines an optimization algorithm based on multiverse theory (master stage) and numerical method of successive approximation (slave stage). The master stage proposes levels to be injected by each distributed generator DC network, slave evaluates impact configur...

In optimization problem, Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO) have been known as good alternative techniques. GA is designed by adopting the natural evolution process, while ACO is inspired by the foraging behaviour of ant species. This paper presents a hybrid GA-ACO for Travelling Salesman Problem (TSP), called Genetic Ant Colony Optimization (GACO). In this metho...