Research and Practice on Curriculum Reform of the Packaging Design Based on the Development Strategy of"Made in China 2025"

In 2015,the Chinese government has put forward the development strategy of"made in China 2025"with Chinese characteristics,adhering to the basic policy of"innovation driven,quality first,green development,structural optimization and talent oriented",and the basic principle of"guided by the market and the government,based on the current and long-term,overall promotion and key breakthrough,independent development and open cooperation".Under the background,for the curriculum characteristics of the Packing Design,the"packaging task-based"teaching model is introduced,and the research and practice of curriculum reform are carried out from three aspects:curriculum content arrangement,curriculum design training and graduation design training,thereby cultivating students'practical ability and innovative spirit,letting students learn to study independently and practice actively,enhancing students'packaging practice ability and employment competitiveness,and training more and more excellent product packaging design talents for"made in China 2025".

Construction of Resilient Functions

Bastd on the relationship between nonlinearity and resiliency of amulti-output function, we present a method for constructing noninterseeling linear codes frompacking design. Through these linear codes, we obtain n-variable, m-output, t-resilient functionswith very high nonlinearity. Their nonlinearities are currently the best results for most of cases.

Multi-objective layout optimization of a satellite module using the Wang-Landau sampling method with local search

The layout design of satellite modules is considered to be NP-hard. It is not only a complex coupled system design problem but also a special multi-objective optimization problem. The greatest challenge in solving this problem is that the function to be optimized is characterized by a multitude of local minima separated by high-energy barriers. The Wang-Landau(WL) sampling method, which is an improved Monte Carlo method, has been successfully applied to solve many optimization problems. In this paper we use the WL sampling method to optimize the layout of a satellite module. To accelerate the search for a global optimal layout, local search(LS) based on the gradient method is executed once the Monte-Carlo sweep produces a new layout. By combining the WL sampling algorithm, the LS method, and heuristic layout update strategies, a hybrid method called WL-LS is proposed to obtain a final layout scheme. Furthermore, to improve significantly the efficiency of the algorithm, we propose an accurate and fast computational method for the overlapping depth between two objects(such as two rectangular objects, two circular objects, or a rectangular object and a circular object) embedding each other. The rectangular objects are placed orthogonally. We test two instances using first 51 and then 53 objects. For both instances, the proposed WL-LS algorithm outperforms methods in the literature. Numerical results show that the WL-LS algorithm is an effective method for layout optimization of satellite modules.