Economic Production Lot Sizing with Periodic Costs and Overtime*

Traditional approaches for modeling economic production lot‐sizing problems assume that a single, fixed equipment setup cost is incurred each time a product is run, regardless of the quantity manufactured. This permits multiple days of production from one production setup. In this paper, we extend the model to consider additional fixed charges, such as cleanup or inspection costs, that are associated with each time period's production. This manufacturing cost structure is common in the food, chemical, and pharmaceutical industries, where process equipment must be sanitized between item changeovers and at the end of each day's production. We propose two mathematical problem formulations and optimization algorithms. The models' unique features include regular time production constraints, a fixed charge for each time period's production, and the availability of overtime production capacity. Experimental results indicate the conditions under which our algorithms' performance is superior to traditional approaches. We also test the procedures on a set of lot‐sizing problems facing a national food processor and document their potential economic benefit.     

Impact of investing in quality improvement on (Q,r, L) model involving the imperfect production process

This paper investigates the impact of quality improvement on the modified lot size reorder point models involving variable lead time and partial backorders. The formulated models include the imperfect production process and an investing option of improving the process quality. The objective is simultaneously optimizing the lot size, reorder point, process quality level and lead time. We first assume that the lead time demand follows a normal distribution, then relax this assumption to consider the distribution-free case where only the mean and standard deviation of lead time demand are known. An algorithm procedure of finding the optimal solution is developed, and two numerical examples are given to illustrate the results.     

New methods for fitting multiple sinusoids from irregularly sampled data

A novel framework is proposed for the estimation of multiple sinusoids from irregularly sampled time series. This spectral analysis problem is addressed as an under-determined inverse problem, where the spectrum is discretized on an arbitrarily thin frequency grid. As we focus on line spectra estimation, the solution must be sparse, i.e. the amplitude of the spectrum must be zero almost everywhere. Such prior information is taken into account within the Bayesian framework. Two models are used to account for the prior sparseness of the solution, namely a Laplace prior and a Bernoulli–Gaussian prior, associated to optimization and stochastic sampling algorithms, respectively. Such approaches are efficient alternatives to usual sequential prewhitening methods, especially in case of strong sampling aliases perturbating the Fourier spectrum. Both methods should be intensively tested on real data sets by physicists.     

Kiefer–Wolfowitz algorithm under quasi-associated random errors

In this article, we study the algorithm of Kiefer–Wolfowitz underquasi-associated random errors. We establish the complete convergence and obtain an exponential bound. Additionally, we build a confidence interval for the minimum. Numerical examples are sketched out to confirm the theoretical results and show the accuracy of the algorithm.     

我国银行客户经理制优化探讨——基于中小企业信贷视角

以中小企业信贷为视角,探讨优化我国银行客户经理制的思路和路径,针对银行客户经理制的组织模式、业务流程、管理制度和作业支持方面提出具体建议。     

间歇用汽负荷的蒸汽优化调度方法

当蒸汽系统中存在着间歇用汽设备时，其用汽负荷将随用汽设备的启停而产生波动．蒸汽负荷的急剧波动不仅影响锅炉的经济运行，而且直接影响蒸汽品质和产品质量．本文提出用数学规划的方法对间歇用汽设备的开启时间进行合理调度，从而使整个系统的用汽负荷趋于均衡．此方法在实际应用中取得了良好的效果．     

交互效应矩阵理论及应用

交互效应矩阵理论,是一种定性与定量相结合的控制理论,用以解决和处理一些运用经典数学的方法难以解决的模糊信息问题.本文将交互效应矩阵理论引入教学控制范畴,研究和分析学校的教学问题.实践证明这是一种行之有效、效果显著的教育控制理论,具有重要的推广价值.     

Integrated retail decisions with multiple selling periods and customer segments: Optimization and insights

Integrating retail decisions on such aspects as assortment, pricing, and inventory greatly improves profitability. We examine a multi-period selling horizon where a retailer jointly optimizes assortment planning, pricing, and inventory decisions for a product line of substitutable products, in a market with multiple customer segments. Focusing on fast-moving retail products, the problem is modeled as a mixed-integer nonlinear program where demand is driven by exogenous consumer reservation prices and endogenous assortment and pricing decisions. A mixed-integer linear reformulation is developed, which enables an exact solution to large problem instances (with up to a hundred products) in manageable times. Empirical evidence is provided in support of a classical deterministic maximum-surplus consumer choice model. Computational results and managerial insights are discussed. We find that the optimal assortment and pricing decisions do not exhibit a simple, intuitive structure that could be analytically characterized, which reflects the usefulness of optimization approaches to numerically identify attractive trade-offs for the decision-maker. We also observe that suboptimal inventory policies significantly decrease profitability, which highlights the importance of integrated decision-making. Finally, we find that the seasonality of consumer preferences and supply costs present an opportunity for boosting the profit via higher inventory levels and wider assortments.     

我国外汇储备:效用最优化及其运用策略

截至2006年9月,我国外汇储备余额为9879亿美元,距万亿美元仅一步之遥,且仍以每月数百亿的速度增长。如何看待和管理高额外汇储备?学术界争锋甚烈,但细察争议,大多“打转”在诸如储汇规模、引汇来源(引资与创汇)和持汇结构等单一层面,既未切换到外汇储备的运用策略(包括间接用汇与直接用汇)层面,更未上升到储汇效用最优化这一全新视角去分析。笔者认为,在我国成为全球最大外汇储备国的背景下,亟需就储汇效用最大化问题展开深入研究;虽然目前对此问题的研究尚属初期,但其指向却相当分明:所谓储汇效用最优化,是指融储汇规模、引汇来源、持汇结构、用汇去向于一体的反复优化的选择行为或动态协调的平衡过程。     

一种新的求解离散型交通网络平衡设计问题的算法

本文提出了一种新的求解离散网络平衡设计二层规划模型的算法。模型求解中,上层问题采用粒子群算法,而下层问题则采用路径生成式logit非平衡交通分配算法。数值结果显示,本文提出的算法可以快速有效地求解这类网络平衡设计二层规划模型。