邮路规划与邮车调度最优化理论研究

对小规模MTSP问题,建立了可精确求解方案的0-1规划模型,并在满足邮政运输需求的前提下给出了最佳方案.问题一首先以县支局、县局为顶点构建无向赋权图,通过Floyd算法求解各局间的最短距离;然后以Fijk为决策变量,以邮车工作时间、车辆运载能力为主要约束,建立以总空载损失费用最小为目标的0-1非线性规划模型,运用规划软件Lingo求解.问题二考虑到市邮路成本,我们采用分层规划策略,首先以市支局、县局为顶点构建无向赋权图,求解出最短路矩阵,建立以邮路运行成本最小为目标的0-1非线性规划模型IIA求解;然后,建立各县区的最短路矩阵,同样建立规划模型IIB求解各县运输方案.问题三由于县局地理位置不变,对区邮路无影响,故以全市各县支局为中心采用逐步最优方法对所有县区支局重新划分;然后采用模型IIB求解.第四问中考虑县局迁移,我们建立近似的启发式算法完成县局选址,并运用规划模型II求解的到新方案.最后,我们对两种区域划分调整方法还进行了定量的分析.     

Target setting: An application to a bank branch network

In this paper we examine the performance of the target setting procedure employed by a large financial institution in Spain to evaluate the operating performance of its branch offices. We begin by evaluating the ability of the branch offices to meet the targets established by bank management. We then evaluate the targets themselves, and we find that the list of targets can be substantially reduced without significant loss or distortion of information to bank management. We then re-evaluate the performance of branch offices on the basis of a reduced set of influential targets.     

Modelling the Flow of Projects Through an Architects' Office

There are many types of organization which have to deal with very variable workloads of project-like activities. They include research laboratories, design organizations and advertising agencies as well as O.R. departments. Their characteristic problem is that of avoiding over-run on due dates and on costs.This is a case study of architects' offices but the other comparable complex queueing systems present similar problems. A simulation model has been developed called OFFice SIMulation. Experiments with the model applied to building design offices have provided new insights into the running of such offices. Also they have raised a number of general questions indicating the dangers of deterministic attitudes in the management of this type of system. These questions are concerned with (i) the trade-off between elapsed time and resources, (ii) loss of formal unified control at the top in favour of informal independent responses at the bottom, (iii) long transient times to introduce change, (iv) loss of the usual benefits of large-scale operations.     

Scheduling trucks in local depots for door-to-door delivery services

A scheduling method is suggested for trucks delivering and picking up freight between branch offices and a regional depot in door-to-door delivery services. As the objective functions, different levels of customer service resulting from different timing of deliveries and pickups to/from branch offices are considered as well as the travel cost of trucks. Useful properties of the optimal timing of deliveries and pickups are derived to reduce the size of the search space significantly. Numerical experiments were conducted to evaluate various algorithms to solve the problem.     

Evaluating the financial performance of bank branches

We evaluate the financial performance of most of the branch offices of a large European savings bank for a recent accounting period. We employ a complementary pair of nonparametric techniques to evaluate their financial performance, in terms of their ability to conserve on the expenses they incur in building their customer bases and providing customer services. We find variation in the ability of branch offices to perform this task, and agreement on the identity of the laggard branches. We then employ parametric techniques to determine that the list of indicators on which their financial performance is evaluated can be reduced without statistically significant loss of information to bank management. Both findings suggest ways in which the bank can increase the profitability of its branch network. A previous version of this paper was presented at CORE, Université Catholique de Louvain, Louvain-la-Neuve, Belgium, where we received many helpful comments from the audience. We are grateful to three referees for their helpful comments as well.     

A Study of the use of Cloakrooms in Office Buildings

Observations of the use of cloakroom accommodation were made in a number of offices and the data collected was incorporated in a computer simulation model of the cloakroom situation. From the output of the model, revised scales of provision are proposed for sanitary accommodation in offices. Unlike the scales currently employed, these offer a consistent standard of service throughout their range.     

Optimal configuration of telephone answering sites in a service industry

The location of facilities, plants, warehouses, distribution centers and the like has always been an important managerial problem. This paper is concerned with the optimal location of telephone answering sites for a non-competitive service organization within the public sector. The answering site network must service the entire United States. The methodological approach taken to addressing the telephone site location problem was integer programming. While the paper to be described herein presents the problem in a conceptual fashion, the approach adopted was in fact the basis of an actual model within a particular national service organization. For reasons of confidentially, the subject organization has requested to remain anonymous.This model and paper presents a conceptual treatment of a portion of a larger study to encompass all aspects of the telephone site location question; that portion directly related to site location and telecommunications. Non-telecommunications aspects such as staffing, space and property considerations, plus other operating cost and non-cost considerations, the latter including organizational and managerial aspects, were also a part of a larger study of which treatment herein will be excluded. The model discussed and developed provided the principal focus and basis for decision making pertaining to this project, primarily due to the large proportion of total costs involved.The study project is national in scope in that callers from all parts of the country have need for various kinds of technical and non-technical information at all times of the year. The location aspect of the telecommunications portion of the telephone model is itself but one aspect of the total problem. Additional aspects include the optimal number of telephone answering sites as well as the appropriate domain (geography served) of each site and the telecommunications (circuitry) configuration at each site.While results of the modelling effort have not been made officially public by the organization under study, it can be stated that the modelling effort resulted in several organization changes including opening and closing of individual offices, domain realignments of new or existing offices, and significant cost savings primarily due to telecommunication cost reductions and increased utilization of telephone answering manpower.     

Swedish employment offices: A new model for evaluating effectiveness

We measure how well Swedish employment offices perform in delivering the services required of them by the Swedish government. In contrast to earlier studies we use a dynamic efficiency framework, which allows us to better model the intertemporal nature of these services, explicitly allowing for placements of intermediate nature across periods. Rather than using second stage analysis to assess the effects of varying local labor market conditions and differences in client characteristics on performance, we include a measure of the office’s expected work load directly in the model. This measure, derived from duration analysis, is designed to capture the variation across offices in resources needed before an average individual can obtain employment. It is estimated from the characteristics of all unemployed individual and local labor market conditions.     

House allocation when availability of houses may change unexpectedly

We study the problem of allocating a set of objects, e.g. houses, tasks, offices to a group of people having preferences over these objects. For various reasons, there may be more or fewer objects than initially planned and allocated. How should such unexpected changes be handled? One way is to declare the initial decision irrelevant and reallocate all available objects. Alternatively, one can use the initial decision as starting point in allocating the new objects. Since both perspectives seem equally reasonable, a natural robustness principle on the rule is that it should produce the same outcome no matter which one is taken. We define two robustness properties based on this idea, pertaining to more objects and fewer objects, respectively.We characterize the family of rules that satisfy mild efficiency, fairness and incentives requirements, together with either one of our robustness properties. They are the family of serial dictatorship rules.     

A Generalized Single Linkage Method for Estimating the Cluster Tree of a Density

The goal of clustering is to detect the presence of distinct groups in a dataset and assign group labels to the observations. Nonparametric clustering is based on the premise that the observations may be regarded as a sample from some underlying density in feature space and that groups correspond to modes of this density. The goal then is to find the modes and assign each observation to the domain of attraction of a mode. The modal structure of a density is summarized by its cluster tree; modes of the density correspond to leaves of the cluster tree. Estimating the cluster tree is the primary goal of nonparametric cluster analysis. We adopt a plug-in approach to cluster tree estimation: estimate the cluster tree of the feature density by the cluster tree of a density estimate. For some density estimates the cluster tree can be computed exactly; for others we have to be content with an approximation. We present a graph-based method that can approximate the cluster tree of any density estimate. Density estimates tend to have spurious modes caused by sampling variability, leading to spurious branches in the graph cluster tree. We propose excess mass as a measure for the size of a branch, reflecting the height of the corresponding peak of the density above the surrounding valley floor as well as its spatial extent. Excess mass can be used as a guide for pruning the graph cluster tree. We point out mathematical and algorithmic connections to single linkage clustering and illustrate our approach on several examples. Supplemental materials for the article, including an R package implementing generalized single linkage clustering, all datasets used in the examples, and R code producing the figures and numerical results, are available online.     

A three-phase algorithm for the cell suppression problem in two-dimensional statistical tables

To obtain full cooperation from respondents, statistical offices must guarantee that confidential data will not be disclosed when their reports are published. For tabular data, cell suppression is one of the preferred techniques to control statistical disclosure. When suppressing only confidential values does not guarantee the desired data protection, it is also necessary to suppress the values in some non-confidential cells. The problem of finding an optimal set of complementary suppressions—the cell suppression problem (CSP)—is NP-hard. We present a three-phase algorithm for the CSP based on a binary relaxation derived from row and column protection conditions. To enforce violated single cell conditions, integer cuts are added to the CSP relaxation. The numerical results obtained in 1410 instances with up to more than 250?000 cells, which were generated to reproduce two classes of real-world data, indicate that the algorithm is quite effective for both classes of instances and that it outperforms state-of-the-art algorithms for one of them.     

Optimal nonparametric estimation of the density of regression errors with finite support

Knowledge of the probability distribution of error in a regression problem plays an important role in verification of an assumed regression model, making inference about predictions, finding optimal regression estimates, suggesting confidence bands and goodness of fit tests as well as in many other issues of the regression analysis. This article is devoted to an optimal estimation of the error probability density in a general heteroscedastic regression model with possibly dependent predictors and regression errors. Neither the design density nor regression function nor scale function is assumed to be known, but they are suppose to be differentiable and an estimated error density is suppose to have a finite support and to be at least twice differentiable. Under this assumption the article proves, for the first time in the literature, that it is possible to estimate the regression error density with the accuracy of an oracle that knows “true” underlying regression errors. Real and simulated examples illustrate importance of the error density estimation as well as the suggested oracle methodology and the method of estimation.     

Permissible boundary prior function as a virtually proper prior density

Regularity conditions for an improper prior function to be regarded as a virtually proper prior density are proposed, and their implications are discussed. The two regularity conditions require that a prior function is defined as a limit of a sequence of proper prior densities and also that the induced posterior density is derived as a smooth limit of the sequence of corresponding posterior densities. This approach is compared with the assumption of a degenerated prior density at an unknown point, which is familiar in the empirical Bayes method. The comparison study extends also to the assumption of an improper prior function discussed separately from any proper prior density. Properties and examples are presented to claim potential usefulness of the proposed notion.     

Modeling eco-behavioral systems

Eco-behavioral systems deal with discrete units of social activity and its immediate environment called behavior settings. These are the naturally-occurring units or ‘standing patterns of behavior’ into which people sort themselves to get on with the business of daily life — retail stores, offices, school classes, religious services, meetings, athletic events, and so on. The concept was originated by the psychologist Roger Barker, who described an entire small community as a system of behavior settings. Barker and his associates showed that behavior setting surveys could be used to measure differences between two communities, one American and one English, in a given year and that surveys of the two communities taken ten years apart could be used to measure social change in each and differences in their patterns of change. They did not attempt formal mathematical models. The present study illustrates some of the basic issues and implications of mathematical modeling of such eco-behavioral systems. Three most important aspects of environment-behavior relations are analyzed here: evolution and change, variety and diversity, and finally efficiency and interdependence. By utilizing the cross-section and time-series data from behavior-setting surveys these models can be directly applied and hence used for predictive and other purposes.     

Connection between the Hadamard and matrix products with an application to matrix-variate Birnbaum-Saunders distributions

In this paper, we establish a connection between the Hadamard product and the usual matrix multiplication. In addition, we study some new properties of the Hadamard product and explore the inverse problem associated with the established connection, which facilitates diverse applications. Furthermore, we propose a matrix-variate generalized Birnbaum-Saunders (GBS) distribution. Three representations of the matrix-variate GBS density are provided, one of them by using the mentioned connection. The main motivation of this article is based on the fact that the representation of the matrix-variate GBS density based on element-by-element specification does not allow matrix transformations. Consequently, some statistical procedures based on this representation, such as multivariate data analysis and statistical shape theory, cannot be performed. For this reason, the primary goal of this work is to obtain a matrix representation of the matrix-variate GBS density that is useful for some statistical applications. When the GBS density is expressed by means of a matrix representation based on the Hadamard product, such a density is defined in terms of the original matrices, as is common for many matrix-variate distributions, allowing matrix transformations to be handled in a natural way and then suitable statistical procedures to be developed.     

Structure function and spectral density of fractal profiles

Spectral density and structure function for fractal profile are analyzed. It is found that the fractal dimension obtained from spectral density is not exactly the same as that obtained from structure function. The fractal dimension of structure function is larger than that of spectral density for small fractal dimension, and is smaller than that of spectral density for larger fractal dimension. The fractal dimension of structure function strongly depends on the spectral density at low and high wave numbers. The spectral density at low wave number affects the structure function at long distance, especially for small fractal dimension. The spectral density at high wave number affects the structure function at short distance, especially for large fractal dimension. This problem is more serious for bifractal profiles. Therefore, in order to obtain a correct fractal dimension, both spectral density and structure function should be checked.     

Nonlinear weighted least squares estimation of a three-parameter Weibull density with a nonparametric start

This paper is concerned with the parameter estimation problem for the three-parameter Weibull density which is widely employed as a model in reliability and lifetime studies. Our approach is a combination of nonparametric and parametric methods. The basic idea is to start with an initial nonparametric density estimate which needs to be as good as possible, and then apply the nonlinear least squares method to estimate the unknown parameters. As a main result, a theorem on the existence of the least squares estimate is obtained. Some simulations are given to show that our approach is satisfactory if the initial density is of good enough quality.     

Predicting stochastic characteristics of generalized eigenvalues via a novel sensitivity-based probability density evolution method

This paper proposes a novel numerical method for predicting the probability density function of generalized eigenvalues in the mechanical vibration system with consideration of uncertainties in structural parameters. The eigenproblem of structural vibration is presented by first and the sensitivity of generalized eigenvalues with respect to structural parameters can be derived. The probability density evolution method is then developed to capture the probability density function of generalized eigenvalues considering uncertain material properties. Within the proposed method, the probability density evolution equation for the generalized eigenvalue problem is established accounting for the sensitivity of generalized eigenvalues with respect to structural parameters. A new variable which connects generalized eigenvalues to structural parameters is then introduced to simplify the original probability density evolution equation. Next, the simplified probability density evolution equation is solved by using the finite difference method with total variation diminishing schemes. Finally, the probability density function as well as the second-order statistical quantities of generalized eigenvalues can be predicted. Numerical examples demonstrate that the proposed method yields results consistent with Monte-Carlo simulation method within significantly less computation time and the coefficients of variation of uncertain parameters as well as the total number of them have remarkable effects on stochastic characteristics of generalized eigenvalues.     

A marginal contribution coefficient for sequences of nonstationary continuous Markov chains

In this work, a set of sequences of information (time series), under nonstationary regime, with continuous space state, discrete time, and a Markovian dependence, is considered. A new model that expresses the marginal transition density function of one sequence as a linear combination of the marginal transition density functions of all sequences in the set is proposed. The coefficients of this combination are denominated marginal contribution coefficients and represent how much each transition density function contributes to the calculation of a chosen transition density function. The proposed coefficient is a marginal coefficient because it can be computed instantaneously, and it may change from one time to another time since all calculations are performed before stationarity is reached. This clearly differentiates the new coefficient from well‐known measures such as the cross‐correlation and the coherence. The idea behind the model is that if a specific sequence has a high marginal contribution for the transition density function from another sequence, the first may be replaced by the latter without losing much information that means that the knowledge of few densities should be enough to recover the overall behaviour. Simulations, considering 2 chains, are presented so as to check the sensitivity of the proposed model. The methodology is also applied to a real data originated from a wire‐drawing machine whose main function is to decrease the transverse diameter of metal wires. The behaviour of the level of acceleration of each bearing in relation to the other ones is then verified.