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Differential evolution (DE) is a very simple and effective stochastic search algorithm, which obtains various performances with different parameter and searching strategy configurations. DE with an individual-dependent mechanism (IDE) is a recently proposed DE variant, which includes an individual-dependent parameter (IDP) setting method and an individual-dependent mutation (IDM) strategy. In this...
Large service providers (SP) who own their computing, storage, and networking resources have the potential to jointly manage their resources to achieve better quality of service and lower cost. Information-centric networking (ICN) exploits in-network caching resource, by unique identification of content objects. Orchestrating cache and networking resources in a coordinated way is the key to the success...
In this paper, we present a class of primal-dual interior-point algorithms for convex quadratic symmetric cone optimization based on a parametric kernel function, which has been introduced for linear optimization. By using Euclidean Jordan algebras, we derive the iteration bounds that match the currently best known iteration bounds for large- and small-update methods, which are as good as the linear...
The basic method of statistic process control is to eliminate variation and put process under statistic control. The negative effect of the method is that it leads to the neglect of the valuable information contained in process variation, thus missing the opportunity for process optimization. But variation is not necessarily harmful, from the biological evolution point of view, variation is the driving...
In this paper we present an infeasible primal-dual interior-point algorithm for linearly constrained convex optimization based on a parametric kernel function, with parameters p isin [0,1] and q ges 1. Numerical test shows that the efficiency of the proposed algorithm and investigates the behavior of the algorithm with different parameters p, q and thetas.
In this paper a primal-dual interior-point algorithm for convex quadratic optimization based on a parametric kernel function, with parameters p isin [0,1] and q ges 1, is presented. The proposed parametric kernel function is of excellent properties which are used both for determining the search directions and measuring the distance between the given iterate and the central path for the algorithm....
In this article we introduce a new quality control model for complex manufacturing system which has the potential to enable enterprise to protect itself from harmful non-conformance in a way like biological system. The model is based on danger theory. In the proposed quality control model, a co-stimulation is necessary to confirm the danger implied by the presence of a detected quality variation,...
Facing with increasing international competition, how to reduce process variability is always one of the major concerns of manufacturing organization. The purpose of this paper is to investigate a data driven optimization model: Process Quality Optimization Model (PQOM) based on Association Rules Mining (ARM) and immune principle to support both staticand dynamic optimization of process quality. Realization...
A fundamental asset of a model-based development process is the capability of providing an automatic implementation of the model that preserves its semantics and, at the same time, makes an efficient use of the resources of the execution platform. The implementation of communication between functional blocks in a synchronous reactive model requires buffering schemes and access procedures at the kernel...
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