The various meta-heuristic techniques for cloud and grid environment are: Ant Colony Optimization (ACO), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Tabu Search, Firefly Algorithm, BAT Algorithm and many more. So this paper represents the two types of meta-heuristic techniques, i.e. BAT algorithm and Genetic Algorithm. The different types of methods which comprise meta-heuristic ...

In this paper, we propose a new parallel genetic a lge rithm (GA), called Extended Distributed Genetic Algorithm (EDGA), for channel routing problem. The EDGA combines the advantages of previous parallel GA models , viz., master/slave GA model and distributed GA model. In EDGA, the root processor executes the conventional genetic algorithm with global selection on total population and the remai...

prediction of the agricultural developmental problems has ever been one of the goals of proper agricultural development, to gain more productions from the minimum resources. the goal of this research is zoning prone area of olive cultivation with two methods: gis and genetic algorithm. also the results have been compared with the current olive cultivation areas in lorestan province and the resu...

in instance-based learning, a training set is given to a classifier for classifying new instances. in practice, not all information in the training set is useful for classifiers. therefore, it is convenient to discard irrelevant instances from the training set. this process is known as instance reduction, which is an important task for classifiers since through this process the time for classif...

Identifying software components is a crucial task in software development. There are a number of methods to identify components in the literature; however, the majority of these methods rely on clustering techniques with expert judgment. In contrast to the previous methods, which have used classical clustering techniques, this paper maps the components identification problem to an optimization ...

−We investigate the performance of a classical constrained optimisation (CCO) algorithm and a constrained optimisation Genetic Algorithm (GA) for solving the Bandwidth Allocation for Virtual Paths (BAVP) problem. We compare throughput, fairness and time complexity of GA-BAVP and CCO-BAVP for several node topologies. The results on maximising the throughput obtained with GA-BAVP and CCOBAVP are ...