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The service composition composing the existing Web services to form new, satisfying different user requirements and value-added composition service has become new application requirement and popular research. The optimization of services composition is a nonlinear multi-objective optimization problem which has been proven to be NP-complete. It is preponderant to settle the multi-objective optimization...
The issue of the guarantee quality of service (QOS) for users can be provided by the advanced reservation. The advanced reservation is a kind of mechanism that can provide the ability to allocate resources for users based on the agreement upon the needs of quality service and increase of the number of accepted users' requests in Grid system. Scheduling and advanced reservation of the resources in...
Linguistic fuzzy modeling in high dimensional regression problems is a challenging topic since conventional linguistic fuzzy rule-based systems suffer from exponential rule explosion when the number of variables and/or data examples becomes high. A good way to face this problem is by searching for a good and simple global structure within the same process, in order to consider the relationships among...
Unit commitment is an important and difficulty aspect of optimal operation of power systems. Because it belongs to be mixed variables programming that is difficult to find the optimal solution in mathematics. This paper presents a new method combining of neighbor search and interior-point method (LS-IP) to solve UC NP-hard problem. The structure of neighborhood is defined and a new way to adjust neighborhood...
This paper addresses dynamic data clustering as an optimization problem and propose techniques for finding optimal (number of) clusters in a multi-dimensional data or feature space. In order to accomplish this objective we first propose two novel techniques, which successfully address several major problems in the field of particle swarm optimization (PSO) and promise a significant breakthrough over...
Aiming at the problem in facial feature location, the Active Shape Models algorithm has no evaluable criterion to judge its convergence, and tend to run into local minimum when using the fixed search scale, and how to choose the scale is always an issue. This paper presents a method based on the whole shape gray grads to evaluate the search effects, and an improved search policy of multiscale. The...
Most optimization algorithms suffer from a significant deterioration in performance as the dimensionality and complexity of the problem search space increases. Also these algorithms, given certain configurations, typically show markedly improved performance on a particular problem only to exhibit poor performance on another. The first issue could be resolved by using a cooperative algorithm to divide...
The inertia weight is often used to control the global exploration and local exploitation abilities of particle swarm optimizers (PSO). In this paper, a group of strategies with multi-stage linearly-decreasing inertia weight (MLDW) is proposed in order to get better balance between the global and local search. Six most commonly used benchmarks are used to evaluate the MLDW strategies on the performance...
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