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Nowadays cloud computing provides an effective way of implementing infrastructure as a service (IaaS). However virtualized data centers still face many challenges, such as low resource utilization of physical machines (PMs) and imbalanced server loads. Virtual machine (VM) consolidation based on live migration allows administrator to dynamically redeploy VMs into PMs for better resource utilization...
Currently, over nine billion things are connected in the Internet of Things (IoT). This number is expected to exceed 20 billion in the near future, and the number of things is quickly increasing, indicating that numerous data will be generated. It is necessary to build an infrastructure to manage the connected things. Cloud computing (CC) has become important in terms of analysis and data storage...
In the past years, the Electrical Utility Industry has been confronted with numerous challenges, which include amongst others, the widespread use of distributed energy resources and a public increase in environmental issues. By optimizing the location of switching devices on the electrical distribution system, an improvement in energy not supplied and in the use of distributed energy resources can...
The most common way of multi-objective optimizations is assigning a weight to each objective and construct a single fitness function. In this method finding of the appropriate weights is the most important problem. The second method, which is not very well-known for power system researchers, is to optimize the objectives independently. Many optimum answers are achieved instead of a single one. These...
We describe a kind of supply chain optimization problem as a commodity stream routing problem upon a stochastic flow network. We divide the optimization problem to two parts: Firstly, establish model to calculate the optimal commodity stream allocation policy on all minimal paths; secondly, convert these allocation policy on all minimal paths to the optimal routing policy on all arcs. A multi-objective...
Today momentary interruptions are an important customer issue and most distribution engineers consider them a reliability issue. This paper considers reliability as all aspects of customer interruptions, including momentary interruptions. A methodology for multiobjective optimization is proposed to minimize SAIFI, SAIDI and MAIFIE indices simultaneously. This goal is achieved considering both the...
The paper analyses the issues behind strategies optimization of an existing automated warehouse for the steelmaking industry. Genetic algorithms are employed to this purpose by deriving a custom chromosome structure as well as ad-hoc crossover and mutation operators. A comparison between three different solutions able to deal with multiobjective optimization are presented: the first approach is based...
Genetic Algorithm (GA) is a non-parametric optimization technique that is frequently used in problems of combinatory nature with discrete or continuous variables. Depending on the evaluation function used this optimization technique may be applied to solve problems containing more than one objective. In treating with multi-objective evaluation functions it is important to have an adequate methodology...
Resource optimization is a very important aspect in cognitive radio network (CRN). It is a typical multi-objective optimization problem. This paper proposes a mixed multi-objective immune cloning genetic algorithm (MMGA) to solve the optimization of resource allocation in CRNs. Based on the genetic algorithm of non-domination sort, the MMGA adds external memory immune operator and cloning operator...
Based on data collected previously on the electricity market of the East China, we use stepwise regression method to find the approximate expression of the active power flow of each power sets on East Chinapsilas certain electrical network. Then classified discussion is carried out according to the difference of the capacity in and out of merit in order to obtain a simple and reasonable rule for calculating...
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