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Task allocation and scheduling in MAS systems utilized genetic algorithm is a focus for more and more computer scholars. Aiming at the low speed of typical genetic algorithm, the global convergence for traditional genetic algorithm, and the local convergence for simulated annealing algorithm, this paper proposes a new task allocation algorithm in multiple Agent systems with the advantages of both...
Scheduling is a very important part of the cloud computing system. This paper introduces an optimized algorithm for task scheduling based on genetic simulated annealing algorithm in cloud computing and its implementation. Algorithm considers the QOS requirements of different type tasks, the QOS parameters are dealt with dimensionless. The algorithm efficiently completes tasks scheduling in the cloud...
A large project in a company is often divided to several subtasks, which would be assigned to different people with variant abilities to the same task. So whether the tasks are scheduled properly would determine the quality or the efficiency of team collaboration. A hybrid particle swarm optimization (PSO) algorithm is putted forward. Subtasks are disassembled from the project by using the task tree...
Task scheduling is one of the key factors in a distributed system. That is, how proper allocating the tasks to the processor of each computer in order to achieve better performance is important. In this problem the reported methods try to minimize Make span and communication cost while maximizing CPU utilization. Since this problem is NP-complete, many genetic algorithms have been proposed. However,...
Making use of several of resource to meet userpsilas request is needed in heterogeneous multiprocessor. It is crucial problem to realize the optimization of utility of resources ensuring of resource balancing. Aiming at the conditions and characteristic of application of multiprocessor system, a quantum clone immunity algorithm was introduced. Application of the algorithm dramatically reduces the...
Parallel test is a new important feature of the future ATS (automatic test system). The optimized parallel test task scheduling is a key problem to the parallel test. In this paper, the genetic algorithm and simulated annealing algorithm are combined effectively to find the multi-UUT (unit-under-test) parallel test tasks array to suffice multiple objectives. The mathematical model and multiple objectives...
Power load forecasting is essential in the task scheduling of every electricity production and distribution facility. This paper studies the application of a variety of tuning techniques for optimizing the least squares support vector machines (LS-SVM) hyper-parameters in a short-term load forecasting problem. Clearly, the construction of any effective and accurate LS-SVM model depends on carefully...
Task scheduling is a NP-hard problem and is an integral part of parallel and distributed computing. This paper combined with the advantages of genetic algorithm and simulated annealing, brings forward a parallel genetic simulated annealing algorithm and applied to solve task scheduling in grid computing. It first generates a new group of individuals through genetic operation such as reproduction,...
Since the task scheduling in grid computing faces a NP-hard problem, it leads very difficult to validate the methods of task scheduling. This paper combined with the advantages of two evaluative algorithms: genetic algorithm and simulated annealing, brings forward an hybrid evaluative algorithm and applied to solve task scheduling problem in grid computing. From the analysis and experiment result,...
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