A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

A steelmaking-continuous casting (SCC) scheduling problem is an example of complex hybrid flow shop scheduling problem (HFSSP) with a strong industrial background. This paper investigates the SCC scheduling problem that involves controllable processing times (CPT) with multiple objectives concerning the total waiting time, earliness/tardiness and adjusting cost. The SCC scheduling problem with CPT is seldom discussed in the existing literature. This study is motivated by the practical situation of a large integrated steel company in which the just-in-time (JIT) and cost-cutting production strategy have become a significant concern. To address this complex HFSSP, the scheduling problem is decomposed into two subproblems: a parallel machine scheduling problem (PMSP) in the last stage and an HFSSP in the upstream stages. First, a hybrid differential evolution (HDE) algorithm combined with a variable neighborhood decomposition search (VNDS) is proposed for the former subproblem. Second, an iterative backward list scheduling (IBLS) algorithm is presented to solve the latter subproblem. The effectiveness of this bi-layer optimization approach is verified by computational experiments on well-designed and real-world scheduling instances. This study provides a new perspective on modeling and solving practical SCC scheduling problems.     

A new DSmT combination rule in open frame of discernment and its application

A new combination rule based on Dezert-Smarandache theory (DSmT) is proposed to deal with the conflict evidence resulting from the non-exhaustivity of the discernment frame. A two-dimensional measure factor in Dempster-Shafer theory (DST) is extended to DSmT to judge the conflict degree between evidence. The original DSmT combination rule or new DSmT combination rule can be selected for fusion according to this degree. Finally, some examples in simultaneous fault diagnosis of motor rotor are given to illustrate the effectiveness of the proposed combination rule.     

基于虚拟组织的桌面云安全访问与共享机制研究

采用云计算技术实现托管式的虚拟桌面一般被称为桌面云。近年来桌面云被认为是云计算最为成熟的应用之一,本文着重研究桌面云安全访问与共享机制。我们使用基于PKI的证书认证建立了虚拟组织,在其上重点研究了虚拟机的创建,远程桌面访问,共享等应用。证书认证等机制可以使得访问更加安全可靠。而通过虚拟组织的信任关系,多个用户可以共享同一个虚拟机。为了确保远程通道的安全,我们采用了OpenVPN来构建虚拟专用网络,对虚拟机的使用者进行认证并对通信进行加密保护。     

基于视频的现实人物运动创作

提出一种根据用户指定的人体运动和观察视角生成真实感视频的方法.首先采集演员进行少数基本运动时的多视角视频数据库,并使用无标记运动捕捉的方法获得任意时刻人体对应的骨骼和3D模型.其次,用户对人体骨架指定运动并设定视角,以此定义目标视频.实验结果验证了文中方法能够利用有限的数据库合成演员在用户指定运动和视角下的真实感视频.     

Learning high-dimensional correspondence via manifold learning and local approximation

The recent years have witnessed a surge of interests of learning high-dimensional correspondence, which is important for both machine learning and neural computation community. Manifold learning–based researches have been considered as one of the most promising directions. In this paper, by analyzing traditional methods, we summarized a new framework for high-dimensional correspondence learning. Within this framework, we also presented a new approach, Local Approximation Maximum Variance Unfolding. Compared with other machine learning–based methods, it could achieve higher accuracy. Besides, we also introduce how to use the proposed framework and methods in a concrete application, cross-system personalization (CSP). Promising experimental results on image alignment and CSP applications are proposed for demonstration.