品种稳定性分析的程序设计与应用

本文介绍了品种稳定性分析适应性参数法的特点和统计方法，编制了相应的ＢＡＳＩＣ程序，同时结合了Ｆａｉｎｌｙ回归分析法，计算方便，提供信息量大，并增加了绘图功能，供农业科研和生产应用。     

A Stochastic Goal Program for Employee Scheduling*

Deterministic goal programs for employee scheduling decisions attempt to minimize expected operating costs by assigning the ideal number of employees to each feasible schedule. For each period in the planning horizon, managers must first determine the amount of labor that should be scheduled for duty. These requirements are often established with marginal analysis techniques, which use estimates for incremental labor costs and shortage expenses. Typically, each period in the planning horizon is evaluated as an independent epoch. An implicit assumption is that individual employees can be assigned to schedules with as little as a single period of work. If this assumption violates local work rules, the labor requirements parameters for the deterministic goal program may be suboptimal. As we show in this research, this well-known limitation can lead to costly staffing and scheduling errors. We propose an employee scheduling model that overcomes this limitation by integrating the labor requirements and scheduling decisions. Instead of a single, externally determined staffing goal for each period, the model uses a probability distribution for the quantity of labor required. The model is free to choose an appropriate staffing level for each period, eliminating the need for a separate goal-setting procedure. In most cases this results in better, less costly decisions. In addition, the proposed model easily accommodates both linear and nonlinear under- and overstaffing penalties. We use simple examples to demonstrate many of these advantages and to illustrate the key techniques necessary to implement our model. We also assess its performance in a study of more than 1,700 simulated stochastic employee scheduling problems.     

Master Scheduling in Assemble-To-Order Environments: A Capacitated Multiobjective Lot-Sizing Model

Basic characteristics of an assemble-to-order environment make effective master scheduling extremely difficult. Limited resource capacities and dynamic customer end-item demand contribute to the complexity of the master production scheduling problem. To gain flexibility and responsiveness within this system, the master production schedule (MPS) focuses at the component level. This research proposes a master scheduling technique for manufactured components which combines a multiobjective capacitated multi-item/multi-stage lot-sizing model with an interactive multiple objective optimization solution procedure. To evaluate the model's performance as a realistic and practical master scheduling tool, this study focuses on the National Cash Register (NCR) electronics manufacturing facility in Columbia, South Carolina.     

Labor Utilization Effects of Labor Scheduling Flexibility Alternatives in a Tour Scheduling Environment

This study used a factorial experimental design and a new modeling methodology to investigate the impact of a number of labor scheduling flexibility alternatives and labor requirements characteristics on labor utilization within a tour scheduling environment. Break-placement flexibility and shift-length flexibility were found to be extremely effective in improving labor utilization for all labor requirement distributions used. Flexibility with respect to the number of days included in a tour schedule resulted in substantial improvement in labor utilization for all labor requirements distributions exhibiting daily and/or weekly variation. Surprisingly, virtually no improvement in labor utilization was achieved for any labor requirement distribution by the removal of requirements for consecutive days off. In addition, almost no improvement was found by allowing the shift start time to vary across the working days included in tours. High labor requirement amplitude was found to have a strong adverse effect on labor utilization while longer operational days were associated with improved labor utilization for all labor requirement distributions. We discuss the implications of these results for service operations management and provide suggestions for future research.     

Vendor Selection with Bundling*

Product bundling has become increasingly prevalent not only in consumer goods but also in the industrial sector. We study a purchasing problem in which a buyer must obtain necessary numbers of various stock items from a variety of vendors who charge different prices, have limited capacities and different levels of quality, and offer bundled products at discounted prices. We examine relationships among different bundling scenarios and show that the most general scenario is one in which free items are given to the buyer when sufficient quantities are purchased. We develop a mixed integer linear program that finds the purchasing strategy for the buyer that minimizes the total purchase cost. We present computational results which indicate that the problem is very tractable to solve optimally on a personal computer with standard optimization software. Finally, three extensions of the model are discussed.     

A Generalization of Wendell's Tolerance Approach to Sensitivity Analysis in Linear Programming

A criticism of linear programming has been that the data which are available in practice are too inexact and unreliable for linear programming to properly work. Managers are therefore concerned with how much actual values may differ from the estimates that were used in the model before the results become irrelevant. Sensitivity analysis emerged to help deal with the uncertainties inherent in the linear programming model. However, the ranges calculated are generally valid only when a single coefficient is varied. An extension of sensitivity analysis, the 100 Percent Rule, allows the simultaneous variation of more than one element in a vector, but does not permit the independent variation of the elements. A tolerance approach to sensitivity analysis enables the consideration of simultaneous and independent change of more than one coefficient. However, the ranges developed are unnecessarily restricted and may be reduced in width to zero when primal or dual degeneracy exists. This paper presents an extension of the tolerance approach which reduces the limitations of both the traditional and tolerance approaches to sensitivity analysis.     

When Restrictive Constraints Are Nonbinding: Illustrations and Implications

For convex and concave mathematical programs restrictive constraints (i.e., their deletion would change the optimum) will always be binding at the optimum, and vice versa. Less well-known is the fact that this property does not hold more generally, even for problems with convex feasible sets. This paper demonstrates the latter fact using numerical illustrations of common classes of problems. It then discusses the implications for public policy analysis, econometric estimation, and solution algorithms.     

Sensitivity Analysis in Linear Programming Models with Common Inputs

The importance of sensitivity analysis information in linear programming has been stressed in the management science literature for some time. Indeed, Gal [3] has devoted an entire text to just this issue. Linear programs with common inputs (cost coefficients or right-hand-side values) present a problem in that classical sensitivity analysis does not allow for the simultaneous changes required to determine the sensitivity of these models to common inputs. We first survey the approaches previously developed for simultaneous-change sensitivity analysis and cast them in the framework of the special common input case. These general techniques are compared to a simple aggregate variable technique that has not received attention in the literature.     

部分状态可见的隐马尔可夫模型状态序列的估计方法

本文考虑了部分状态可见的隐马尔可夫模型的状态序列估计问题,在分析了现有算法无法合理估计状态路径之后,以状态转移概率、观测概率和可见状态作为先验信息,通过贝叶斯分析计算可见状态前后向状态的后验概率,并给出初始条件和递推公式,运用动态规划递推得到每个观测值对应的最可能状态以及最可能的状态路径。最后,本文给出一个系统故障识别的应用例子,验证了所设计算法的可行性。     

DEGENERACY AND THE (MIS)INTERPRETATION OF SENSITIVITY ANALYSIS IN LINEAR PROGRAMMING

Under conditions of degeneracy, sensitivity analysis information such as cost and right-hand-side ranges, which are produced by standard linear programming procedures used in commercial codes, can be misleading. From a managerial perspective, the interpretation of such information can be erroneous. In this paper we present these problems, explain their occurence with elementary examples, and discuss procedures for their resolution.