In cloud computing, an important concern is to allocate the available resources of service nodes requested tasks on demand and make objective function optimum, i.e., maximizing resource utilization, payoffs bandwidth. This paper proposes a hierarchical multi-agent optimization (HMAO) algorithm in order maximize utilization bandwidth cost minimum for computing. The proposed HMAO combination gene...

The predictive hierarchical level of detail optimization algorithm of Mason and Blake is experimentally evaluated in the form of a practical application to hierarchical radiosity. In a novel approach the recursively subdivided patch hierarchy generated by a perceptually refined hierarchical radiosity algorithm is treated as a hierarchical level of detail scene description. In this way we use th...

The objective of this contribution is to propose a multilevel-hierarchical approach to the MINLP synthesis of process flowsheets. Following a hierarchical strategy, the designer can postulate the superstructure at different levels of representation of flowsheet alternatives and model it at the corresponding level of aggregation and complexity. By the use of the prcscrcening procedure the supers...

The efficiency of a large hierarchical organisation is simulated on Barabási-Albert networks, when each needed link leads to a loss of information. The optimum is found at a finite network size, corresponding to about five hierarchical layers, provided a cost for building the network is included in our optimization.

In this paper a new “hierarchical” evolutionary approach to solving multi-objective optimization problems is introduced. The results of experiments with standard multi-objective test problems, which were aimed at comparing “hierarchical” and “classical” versions of multiobjective evolutionary algorithms, show that the proposed approach is a very promising technique.