Application of the integrated framework for the plant layout evaluation problem

During the past two decades, there was not enough research effort spent to study the plant layout evaluation problem compared with that in the plant layout design problem. Only lengthy criterion sets with little structure were proposed for evaluation purpose. Very few quantitative indices were developed for measuring the impacts resulting from the criteria. In addition, there was no reasonable mechanism available to integrate the criteria and indices to obtain a score for each layout alternative. Therefore, an integrated framework for the plant layout evaluation problem is proposed to overcome these three drawbacks. This framework includes a structured criterion set having 18 criteria represented by a three-level hierarchical structure, the corresponding quantitative and qualitative indices for the criteria, and the integration methodology. This paper presents the integration methodology. Six essential issues in developing the integration methodology are discussed (i.e., user flexibility, method of weight assignment, normalization of index values, preceding direction of integration process, insensitivity to intermediate changes, data deficiency and information imbalance). The characteristics of criteria and indices are utilized to reduce the integration effort. For example, the efforts spent in pairwise comparisons of criteria and alternative-criterion comparisons usually seen in the Analytic Hierarchy Process (AHP) are greatly reduced. The application of the integrated framework to two industrial cases including an electronic equipment manufacturer and a home furnishing manufacturer demonstrates the applicability of the research results.     

含定性因子的二阶Scheff′e模型多目标最优设计北大核心

在实际的很多情形中,混料试验都具有多个目标,且响应变量不仅受到各分量的影响,还会受到其他定性因子变量的影响.文中基于一类含定性因子的混料模型,通过求解效率和极值得到多目标最优设计,并证明了该设计满足相应组合最优性.实例证明,该方法同样适用于3个或更多目标优化设计问题.     

On the multi-component layout design with inertial force

The purpose of this paper is to introduce inertial forces into the proposed integrated layout optimization method designing the multi-component systems. Considering a complex packing system for which several components will be placed in a container of specific shape, the aim of the design procedure is to find the optimal location and orientation of each component, as well as the configuration of the structure that supports and interconnects the components. On the one hand, the Finite-circle Method (FCM) is used to avoid the components overlaps, and also overlaps between components and the design domain boundaries. One the other hand, the optimal material layout of the supporting structure in the design domain is designed by topology optimization. A consistent material interpolation scheme between element stiffness and inertial load is presented to avoid the singularity of localized deformation due to the presence of design dependent inertial loading when the element stiffness and the involved inertial load are weakened with the element material removal. The tested numerical example shows the proposed methods extend the actual concept of topology optimization and are efficient to generate reasonable design patterns.     

Supplier selection using axiomatic fuzzy set and TOPSIS methodology in supply chain management

The current paper presents a comprehensive methodology for supplier selection. In the first stage, the linguistic values expressed as trapezoidal fuzzy numbers are used to assess the weights of the criteria. The Axiomatic Fuzzy Set clustering (AFS) method, which handles ambiguity and fuzziness in the supplier selection problem effectively, is applied to cluster the suppliers and evaluate each potential supplier that aims at obtaining initial supplier ranking. In the second stage, the Fuzzy Analytic Hierarchy Process (FAHP) model is constructed to determine the weight of various quantitative and qualitative criteria. To address multiple decision criteria in supplier ranking, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is employed to select the final suppliers. A numerical example composed of 30 suppliers and 6 criteria is studied, and the experimental results show that the proposed evaluation framework is suitable for supplier selection decisions even with the dependent criteria/attributes.     

Applying GIS and Combinatorial Optimization to Fiber Deployment Plans

A decision-support system for the Fiber Deployment Plan problem is developed for the telephone cable network design in the telecommunications industry. The system employs a Geographic Information System (GIS) and uses combinatorial optimization techniques as its components. A mathematical combinatorial optimization model is formulated for the problem and a heuristic solution procedure is developed for the model. A GIS within the ESRI Arc/INFO and ArcView environment is used to provide data needed to build the mathematical combinatorial optimization model and to furnish an interface between the users and computers in data input and in solution result display. Combinatorial optimization techniques are used in the heuristic solution procedure to find good solutions for the optimization model. The developed decision-support system has been used to real life problems and has resulted in tremendous improvements in the telephone cable network design process. The user is completely satisfied with the performance of the system.     

The research on optimization of auto supply chain network robust model under macroeconomic fluctuations

Considering the uncertainty of the macroeconomic environment, the robust optimization method is studied for constructing and designing the automotive supply chain network, and based on the definition of robust solution a robust optimization model is built for integrated supply chain network design that consists of supplier selection problem and facility location–distribution problem. The tabu search algorithm is proposed for supply chain node configuration, analyzing the influence of the level of uncertainty on robust results, and by comparing the performance of supply chain network design through the stochastic programming model and robustness optimize model, on this basis, determining the rational layout of supply chain network under macroeconomic fluctuations. At last the contrastive test result validates that the performance of tabu search algorithm is outstanding on convergence and computational time. Meanwhile it is indicated that the robust optimization model can reduce investment risks effectively when it is applied to supply chain network design.     

寻路行为策略的进化博弈分析

针对我国交通枢纽站中乘客的寻路行为,建立了初访者群体之间以及初访者与熟悉者群体间的博弈模型及其复制动力学方程,并对复制动态做了分析和讨论,得出模型中博弈双方的进化稳定策略。研究结果表明枢纽站内初访者、初访者与熟悉者在有限理性基础上得到的进化稳定策略与标识布设的合理性有关,提出了改进标识布设以推进积极寻路行为发生的合理对策和建议。     

Assessment of transmission of the shear stress in potted anchors for composite rods 1. Sleeve of constant thickness

The key problem facing the application of fiber-reinforced polymer (FRP) stay cables and tendons is the anchorage. Potted (bond-type) anchors have been used more extensively than anchors of any other type. The main aim in the design of anchors is to minimize the peak shear stress at the FRP rod-pottant interface. To this end, parametric analyses of the stress state in the anchors are carried out. Since parametric studies can not be easily performed by the finite-element method, an analytical model of the anchor is proposed. The model involves significant simplifying assumptions and allows one to obtain a relatively simple analytical solution for shear-stress distributions at the FRP rod-pottant interface. The use of this solution at various boundary conditions and various geometrical and mechanical parameters of anchor components enables one to search for and evaluate, at least qualitatively, different methods for decreasing the peak interfacial shear stress in the anchor. In this part of the investigation, an anchor consisting of a sleeve of constant thickness is considered. Russian tanslation published in Mekhanika Kompozitnykh Materialov, Vol. 45, No. 3, pp. 321-346, May-June, 2009.     

云计算环境资源监控系统研究

为保障云计算平台的可靠性,基于Ganglia,采用Eucalyptus开源云平台,提出了云计算平台资源监控系统架构.从总体结构、监控信息处理流程等多个方面对监控系统进行了详细阐述,提出了动态更换虚拟机簇头的算法,并对算法与原型系统进行了验证和性能评测.分析与评测结果表明,所提系统能够适用于云计算环境资源信息的实时监测与预警,具备系统开销较低,用户接口友好的特点,能准确反映系统、虚拟机的负载信息,有助于云计算系统服务可靠性的提升.簇头动态更换算法能及时发现失效的簇头并更换为更健壮的虚拟机,保证了监测系统的正常运行.     

Quantitative and qualitative indices for the plant layout evaluation problem

In the past two decades, the researchers used to develop simulation models or mathematical programming models to estimate the performance measures of a production system which may or may not include the considerations of layout design, rather than develop indices specifically for evaluating a layout alternative. These models usually ask for very detailed information. Most of them involve oversimplifying assumptions and request overwhelming computational efforts such that they cannot be manipulated with ease in practice. The limitations and deficiencies of previous indices and performance measures include: parameters hard to obtain; inappropriate detailed data requirement; much effort to obtain little accuracy improvement; data available after operations start; no generic approach and no clear validation provided. To overcome these deficiencies, the generic approaches for developing quantitative and qualitative indices are provided and new indices for the flow criterion group and environment criterion group are presented. The parameters of each index are easier to obtain and do not require much effort on data collection. The validations of each quantitative index with examples are also provided. The generic approaches also allow the users to revise the indices according to the specific case considered.     

Penalized Estimation in Large-Scale Generalized Linear Array Models

Large-scale generalized linear array models (GLAMs) can be challenging to fit. Computation and storage of its tensor product design matrix can be impossible due to time and memory constraints, and previously considered design matrix free algorithms do not scale well with the dimension of the parameter vector. A new design matrix free algorithm is proposed for computing the penalized maximum likelihood estimate for GLAMs, which, in particular, handles nondifferentiable penalty functions. The proposed algorithm is implemented and available via the R package glamlasso. It combines several ideas—previously considered separately—to obtain sparse estimates while at the same time efficiently exploiting the GLAM structure. In this article, the convergence of the algorithm is treated and the performance of its implementation is investigated and compared to that of glmnet on simulated as well as real data. It is shown that the computation time for glamlasso scales favorably with the size of the problem when compared to glmnet. Supplementary materials, in the form of R code, data and visualizations of results, are available online.     

An effective Markov based approach for calculating the Limit Matrix in the analytic network process

Analytic network process is a multiple criteria decision analysis (MCDA) method that aids decision makers to choose among a number of possible alternatives or prioritize the criteria for making a decision in terms of importance. It handles both qualitative and quantitative criteria, that are compared in pairs, in order to forge a best compromise answer according to the different criteria and influences involved. The method has been widely applied and the literature review reveals a rising trend of ANP-related articles. The ‘power’ matrix method, a procedure necessary for the stability of the decision system, is one of the critical calculations in the mathematical part of the method. The present study proposes an alternative mathematical approach that is based on Markov chain processes and the well-known Gauss-Jordan elimination. The new approach obtains practically the same results as the power matrix method, requires slightly less time and number of calculations and handles effectively cyclic supermatrices, optimizing thus the whole procedure.     

Fuzzy optimization approach to component selection of fault-tolerant software system

In developing software systems, a manager’s goal is to design software using limited resources and meet the user requirements. One of the important user requirements concerns the reliability of the software. The decision to choose the right software modules (components) becomes extremely difficult because of the number of parameters to be considered while making the decision. If suitable components are not available, then the decision process is further complicated with build versus buy decisions. In this paper, we have formulated a fuzzy multi-objective approach to optimal decision “build-or-buy” for component selection for a fault-tolerant modular software system under the consensus recovery block scheme. A joint optimization model is formulated where the two objectives are maximization of system reliability and minimization of the system cost with a constraint on delivery time. An example of developing a retail system for small-and-medium-size enterprises is used to illustrate the proposed methodology.     

Bayesian inference on longitudinal-survival data with multiple features

The modeling of longitudinal and survival data is an active research area. Most of researches focus on improving the estimating efficiency but ignore many data features frequently encountered in practice. In this article, we develop a joint model that concurrently accounting for longitudinal-survival data with multiple features. Specifically, our joint model handles skewness, limit of detection, missingness and measurement errors in covariates which are typical observed in the collection of longitudinal-survival data from many studies. We employ a Bayesian approach for making inference on the joint model. The proposed model and method are applied to an AIDS study. A few alternative models under different conditions are compared. Some interesting results are reported. Simulation studies are conducted to assess the performance of the proposed methods.     

考虑繁忙率的多时段救护车优化布局研究

救护车布局对院前急救服务中需求的响应具有决定性作用。本文重点研究了考虑繁忙率的多时段救护车优化布局问题,在传统双覆盖模型基础上引入救护车繁忙率因素,提出改进后的双覆盖模型。首先计算考虑繁忙率的期望覆盖需求量,进而结合实际,将一天以早晚高峰划分为5个时段,探究不同时段下繁忙率差异带来的不同布局方案。以上海市松江区2014年数据为例,应用改进后的模型进行了系统深入的实证研究,并绘制繁忙率对需求覆盖率的影响曲线。结果表明,本文提出的布局方案比实际方案得到的期望覆盖需求量提高了3.19%,比传统双覆盖模型得到的期望覆盖需求量提高了0.54%,证明了改进后模型的有效性;需求覆盖率曲线随繁忙率增加而下降,与实际意义相符。该方法能够直观简洁地得出救护车布局方案,利于院前急救服务水平的提升,为社会安全提供有力保障。     

一种基于用户识别特征模型的中医药健康养老信息推送算法

通过分析传统协同过滤算法的优缺点,设计构建用户识别特征模型,并提出基于用户识别特征模型的协同过滤算法,将经典协同过滤算法与基于用户识别特征模型的协同过滤算法进行比较试验,分析基于用户识别特征模型的协同过滤算法相对于经典协同算法的优势,进而证明其能够在中医药健康养老信息的推送过程中提高效率。     

A clone-based graphical modeler and mathematical model generator for optimal production planning in process industries

This paper outlines a visually interactive graphical modeling approach for process type production systems, with hidden generation of complex optimization models for production planning. The proposed system lets the users build a graphical model of the production system with one-to-one clones of its production units through its interactive visual interface, accepts production-specific data for its components, and finally, internally generates and solves its mathematical programming model without any interaction from the user. This “clone-based” modeling approach allows the continued use of optimization models with minimal mathematical programming understanding, as generation of mathematical model by clones is hidden and automatic, therefore maintenance-free: Updating graphical production system models is enough for renewing internal optimization models. The concept is demonstrated in this paper with a linear programming prototype developed for a petroleum refinery.     

A modified Physarum-inspired model for the user equilibrium traffic assignment problem

The user equilibrium traffic assignment principle is very important in the traffic assignment problem. Mathematical programming models are designed to solve the user equilibrium problem in traditional algorithms. Recently, the Physarum shows the ability to address the user equilibrium and system optimization traffic assignment problems. However, the Physarum model are not efficient in real traffic networks with two-way traffic characteristics and multiple origin–destination pairs. In this article, a modified Physarum-inspired model for the user equilibrium problem is proposed. By decomposing traffic flux based on origin nodes, the traffic flux from different origin–destination pairs can be distinguished in the proposed model. The Physarum can obtain the equilibrium traffic flux when no shorter path can be discovered between each origin–destination pair. Finally, numerical examples demonstrate the rationality and convergence properties of the proposed model.     

基于改进粒子群算法V型非传统布局仓库通道优化设计

V型仓储布局是一种典型的非传统布局方式,针对V型布局主通道设计的问题,将主通道抽象为若干个点连接而成的折线通道,每条拣货通道按物动量大小对仓库进行分区,采用更加符合实际的存取货物作业的概率不相等的非完全随机存储策略,建立最小化平均拣货距离的仓库主通道设计数学优化模型。其次,设计了基于极值扰动算子的改进粒子群优化算法(EDO-PSO)进行算法求解,利用极值扰动算子解决易陷入局部最优问题,采用并行深度搜索策略,提高算法性能,并用Benchmark函数与其他改进PSO算法对比验证算法性能。最后,结合具体实验数据仿真分析,计算结果表明,该方法在相同货位分配策略下,能有效缩短总拣货距离,验证了方法的有效性。     

带有不可忽略缺失数据的广义部分线性模型的贝叶斯分析

广义部分线性模型是广义线性模型和部分线性模型的推广,是一种应用广泛的半参数模型.本文讨论的是该模型在线性协变量和响应变量均存在非随机缺失数据情形下参数的Bayes估计和基于Bayes因子的模型选择问题,在分析过程中,采用了惩罚样条来估计模型中的非参数成分,并建立了Bayes层次模型;为了解决Gibbs抽样过程中因参数高度相关带来的混合性差以及因维数增加导致出现不稳定性的问题,引入了潜变量做为添加数据并应用了压缩Gibbs抽样方法,改进了收敛性;同时,为了避免计算多重积分,利用了M-H算法估计边缘密度函数后计算Bayes因子,为模型的选择比较提供了一种准则.最后,通过模拟和实例验证了所给方法的有效性.