Authors: Zhan Peng Xie, Chao Yong Zhang, Xin Yu Shao, Yong Yin
Abstract: In this paper, a hybrid methodology that incorporates a simulated annealing (SA) approach into the framework of variable neighborhood search (VNS) is proposed to solve the blocking flow shop scheduling problem with the total flow time minimization. The proposed hybrid algorithm adopts SA as the local search method in the third stage of VNS, and uses a perturbation mechanism consisting of three neighborhood operators in VNS to diversify the search. To enhance the intensification search, best-insert operator is adopted to generate the neighbors in SA. To evaluate the performance of the proposed hybrid algorithm, computational experiments and comparisons were conducted on the well-known Taillard’s benchmark problems. The computational results and comparisons validate the effectiveness of the proposed algorithm.
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Authors: Jie Yu Wu, Xin Yu Shao, Hai Ping Zhu
Abstract: A wireless sensor network (WSN) is a large collection of sensor nodes with limited power supply and constrained computational capability. Clustering routing method in wireless sensor networks has been considered as an important field of research recently to prolong the network lifetime of WSNs. We present a novel clustering method that can balance the energy consumption and extend the lifetime of WSN. Network nodes can be divided into densely connected subgroups through the algorithm of detecting community structure in complex networks. Moreover, the role of cluster-head is scheduled among the cluster members according to the residual energy of nodes, and then the cluster heads send the data to the sink directly. Based on the community clustering strategy, a novel routing protocol, called community structure clustering routing protocol (CSCR), has been raised for WSN. Performance evaluation has shown that the proposed method can achieve improvement compared with LEACH and SEP.
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Authors: Zai Lin Guan, Chuang Jian Wang, Yun Feng Wu, Xin Yu Shao
Abstract: Digital Factory (DF) technology is one of the most important part of manufacturer enterprise information systems, its core technology is modeling & simulation. This paper introduced the digital factory concept and its functions with multi-level multi-resolution modeling and simulation method; we established a new framework of the digital factory technology. It combines with the features of DF and simulation technology which expands the development of DF and application of simulation technology. A case was taken to show the feasibility of multi-level modeling & multi-resolution simulation technology attaching to the DF technology.
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Authors: Dao Yuan Yu, San Qiang Zhang, Xin Yu Shao, Sheng Qiang Liu, Yu Hui Tian
Abstract: This paper proposes a new algorithm of gravity-like mechanism and a multistage buffer for the car sequencing problem. The algorithm utilizes the principle of gravity and codes the cars as particles, which can achieve the ordering by the gravity of particles themselves in the sequencing buffer. The Petri net model of the Buffer is proposed and a car sequencing problem is analyzed as an example, the results prove that the algorithm and the buffer can perform well in car sequencing problem.
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Authors: M. Xiao, Liang Gao, Hao Bo Qiu, Xin Yu Shao, Xue Zheng Chu
Abstract: This paper concentrates on the computational challenge in multidisciplinary design optimization (MDO) and a comprehensive strategy combining enhanced collaborative optimization (ECO) and kriging approximation models is introduced. In this strategy, the computational and organizational advantages of original collaborative optimization (CO) are inherited by ECO, which can satisfy the strengthened consistency requirements. Kriging approximation models are constructed to replace high-fidelity simulation models in individual disciplines and reduce the expensive computational cost in practical MDO problems. The proposed methodology is demonstrated by solving the classical speed reducer design problem. The better results indicate that ECO using kriging approximation models can achieve a considerable reduction of computational expense while guaranteeing the accuracy of optimal solutions with efficient convergence.
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Authors: Wei Zhou, Yun Qing Rao, Xin Yu Shao, Bing Gang Wang
Abstract: Configurable MES is a hot attention in today’s industry. In this work, we present a MES model based on a production process modeling method. With the workflow management technology, a configurable MES framework is introduced and some important implementation methods such as production process modeler, activity script language and production process scheduler are presented. A successful application of an automobile engine assembly line shows that this model is useful and effective.
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Authors: Hao Bo Qiu, Chao Yong Zhang, Ping Jiang, Xin Yu Shao
Abstract: Group decision-making is one of the most important issues in product development. In
order to tackle the vague and sometimes conflicting decision data, this paper presents a new approach
based on fuzzy similarity and fuzzy compromise to deal with the fuzzy nature of group decisions. In
the proposed method, a modified fuzzy Analytical Hierarchy Process method is used to get the
criterion weights, a novel consensus aggregation algorithm is given to obtain the conflict-free results,
and an improved compromise decision means is utilized to calculate the utilities of alternatives.
Finally an integrated product development solution evaluation process is illustrated as a numerical
example, and the corresponding software package is also developed.
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Authors: L. Zhang, Xin Yu Shao, Liang Gao, Wu Tao
Abstract: The process of parameter choosing in vehicle overall design is a process of collaboration
design, and is also a process of group decision optimization. The degree of cooperation and level of
experts become the crucial standards in Computer Supported Collaborative Design because many
decision-makers participating in the design process have different expertise and goals. This paper
describes vehicle overall design parameter selection with a Multi-Objective Decision-Making
optimization model, presents the concepts of non-cooperation degree and non-specialty degree, and
uses entropy to describe the model. Furthermore, Particle Swarm Optimization (PSO) algorithm is
employed to resolve the model and to get optimal parameter. In addition, we propose an effective
expert system based on the model and actual design process. Finally, the effect of the non-cooperation
degree and non-specialty degree on the result is discussed and the sensitivity of the proposed system
analyzed in this paper.
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Authors: Xin Yu Shao, K. Lin, Liang Gao, Hao Bo Qiu
Abstract: Computer supported collaborative work (CSCW) technology is used to solve the
resource-sharing problems in collaborative design, analysis, and manufacture. To address this need, a
system called CollabVue for collaborative product design between designers and manufacturers is
proposed in this study. This paper first introduces the framework of tolerance analysis system based
on CollabVue, and then discusses the utilization of geometric topology information in 3D model to
resolve the problem of dimension information input and the related specific operations. Based on
object-oriented technology, a new data structure to interactively pick up and store dimension
information is established. Finally the model uses iterative method to compute technological
dimension chain equation.
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Authors: Xin Yu Shao, Xue Zheng Chu, Liang Gao, Hao Bo Qiu
Abstract: Uncertainty in design and simulation affects the quality of product directly during the
process of MDO, which should be considered to help designers to make the design decisions,
especially at conceptual design stage. In traditional approaches, this uncertainty is ignored in the hope
that it is not significant to the decision making. In this investigation, firstly, three main uncertainties in
MDO of conceptual design are pointed out and carefully analyzed. Then, an innovative methodology
integrating extract knowledge and probabilistic method to manage these uncertainties is presented.
Considering practical application and eliminating the uncertainty in configuration, we propose a
promising method combining Fuzzy c-means algorithm (FCM) and Rough Sets theory (RST) to
deduce the configuration rule. Furthermore, probabilistic kriging model is utilized as an
approximation model to reduce global computational expense of complex product. Sensitivity
analysis (SA) is used to reduce uncertainty of inputs of simulation, and mean square error (MSE) is
employed to assess model error to reduce model uncertainty. Finally, the validity and necessity of this
methodology are demonstrated through the conceptual design of bulk carrier.
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