The management of services is the kernel content of service-oriented manufacturing. However, it is difficult to realise the integration and optimisation of services in an open environment, which contains large amounts randomicity and uncertainty. The key problem is how to realise the optimal service selection and composition. In this article, the comprehensive performance evaluation metrics for service-oriented manufacturing network is proposed, which combines the key performance indicators of services in business, service and implementation level. The performance evaluation model is brought forward to analyse the local and global performance. An uncertainty and genetic algorithm-based method is developed to realise the optimal service selection and composition in effective and efficient way.
High-Q dielectric materials ilmenite MgTiO 3 , columbite MgNb 2 O 6 and cubic perovskite Ba 3 NiTa 2 O 9 with negative temperature coefficient of resonant frequency (s f ) were selected as candidates for compensating the s f of hexagonal perovskite Ba 8 ZnTa 6 O 24 . X-ray diffraction data shows that Ba 8 ZnTa 6 O 24 coexists with Ba 3 NiTa 2 O 9 but is not compatible with MgTiO 3 and MgNb 2 O 6 at high temperature. The s f for the mixed hexagonal/cubic perovskite Ba 8 ZnTa 6 O 24 -Ba 3 NiTa 2 O 9 system is tunable via the temperature compensation effect and its quality factor may be improved via annealing the ceramics at high temperature to enhance the cation ordering in the cubic component. Permittivity e r * 22-25, Q9f [ 30,000 GHz and tunable s f within ±10 ppm/°C were achieved in the range of about 50-80 wt% Ba 3-NiTa 2 O 9 for the hexagonal/cubic perovskite composite Ba 8 ZnTa 6 O 24 -Ba 3 NiTa 2 O 9 ceramics, which is suitable for the application as dielectric resonators and filters.
A new evolutionary algorithm, which can contract search space based on partial ordering relation and is designed to solve nonlinear programming(NLP), is proposed in this paper. Firstly, partial ordering relation is used for evaluating individual, which ensures individual competition more impartial. Secondly, by taking advantage of the incomplete evolution, which provides good individuals in short time, we can locate regions of optimal solutions and contract the search space and thus reduce the search space and increase the convergence rate. Thirdly, we prove the algorithm can find optimal solutions. At last, the algorithm can be paralleled easily. Numerical experiments demonstrate that our techniques are superior to some other methods in terms of solution quality and robustness.
This paper presents a new approach for the management and engineering of IT-enabled services. Based on the analysis of several real world application scenarios, we propose a "deep structure" for ITenabled service management. We introduce the concept of a business artifact in defining this deep structure. We leverage this deep structure in conjunction with Representational State Transfer (REST) to design and build a platform for service management. Our approach radically simplifies the management and engineering of IT-enabled services and provides a highly flexible and end-user configurable system for service management.
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