An EOQ model for perishable products with discounted selling price and stock dependent demand

A single item economic order quantity model is considered in which the demand is stock dependent. After a certain time the product starts to deteriorate and due to visualization effect and other aspects of deterioration the demand becomes constant. In that situation a discount on selling price provides significant increment in demand rate. In this paper we investigate how much discount on selling price may be given during deterioration to maximize the profit per unit time and whether a pre-deterioration discount affects the unit profit or not. A mathematical model is developed incorporating both pre- and post deterioration discounts on unit selling price, where analytical results reveal some important characteristics of discount structure. A numerical example is presented and sensitivity analysis of the model is carried out.     

模糊随机需求的连续盘点存储策略研究

考虑到需求的模糊随机性,建立模糊随机需求情况下连续盘点存储策略的模糊随机成本模型。利用模糊随机变量的期望值理论,推导出了其成本期望值模型的解析表达式,进而给出了最优再订货点所属区间的判别条件以及最优再订货点和经济订货量的计算式;基于此,设计了一模糊随机需求的连续盘点最优存储策略算法。最后结合数值算例,分析了模糊随机需求概率分布及缺货成本对最优存储策略的影响。     

加权拟合直线方程法在旅游需求预测中的应用

应用加权拟合直线方程法对哈尔滨市旅游需求进行预测,并通过实际旅游人数进行验证、探讨此方法的有效性.     

基于不对称需求信息的数量折扣设计

通过建立数量折扣设计优化模型,利用委托代理理论分别分析了完全和不完全需求信息条件下,商品供应商如何为一群异质的零售商制定价格政策,实现其中望利润的最大化.在完全需求信息条件下,单一价格就能使供应商实现利润最大化;而在需求信息为不对称条件下,逆向选择使单一价格失效,此时,数量折扣是一种能够有效增加零售商订货量的激励方式.     

价格和库存均影响需求、部分拖后供给的易变质品生产库存

考虑产品的需求率受库存和销售价格的影响,拖后供给因子与需求得到满足的实际等待时间有关,建立了易变质品生产库存模型,给出了寻求最优生产策略和销售价格的方法,并分析参数变化对于平均利润、销售价格和服务率的影响.     

基于小波神经网络的中国能源需求预测模型

通过分析影响我国能源需求的主要因素,建立了基于小波神经网络的需求预测模型.采用定性与定量相结合的方式,分析了影响我国能源需求的主要因素,通过将人口总数、GDP、产业结构变化以及能源消费量的一阶滞后作为输入变量,建立基于小波神经网络的我国能源需求非线性预测模型.实验结果表明,该非线性预测模型与多元回归模型相比更加合理,具有更高的预测精度.     

Entropic order quantity (EnOQ) model for deteriorating items

Jaber et al. [M.Y. Jaber, R.Y. Nuwayhid, M.A. Rosen, Price-driven economic order systems from a thermodynamic point of view, Int. J. Prod. Res. 42 (24) (2004) 5167–5184] suggested that it might be possible to improve production systems performance by applying the first and second laws of thermodynamics to reduce system entropy (or disorder). They then used these laws to modify the economic order quantity (EOQ) model to derive an equivalent entropic order quantity (EnOQ). The results suggested that larger quantities should be ordered than is suggested by the classical EOQ model.     

Impact of information sharing and lead time on bullwhip effect and on-hand inventory

This work analyzes a two echelon (warehouse–retailer) serial supply chain to study the impact of information sharing (IS) and lead time on bullwhip effect and on-hand inventory. The customer demand at the retailer is assumed to be an autoregressive (AR(1)) process. Both the echelons use a minimum mean squared error (MMSE) model for forecasting lead time demand (LTD), and follow an adaptive base-stock inventory policy to determine their respective order quantities. For the cases of without IS and inter as well as intra echelon IS, expressions for the bullwhip effect and on-hand inventory for the warehouse are obtained, considering deterministic lead-time. The results are compared with the previous research work and an easy analysis of the various bullwhip effect expressions under different scenarios, is done to understand the impact of IS on the bullwhip effect phenomenon. It is shown that some part of bullwhip effect will always remain even after sharing both inter as well as intra echelon information. Further, with the help of a numerical example it is shown that the lead time reduction is more beneficial in comparison to the sharing of information in terms of reduction in the bullwhip effect phenomenon.     

Alternative formulations of a combined trip generation,trip distribution,modal split,and trip assignment model

The traditional four-step model has been widely used in travel demand forecasting by considering trip generation, trip distribution, modal split and traffic assignment sequentially in a fixed order. However, this sequential approach suffers from the inconsistency among the level-of-service and flow values in each step of the procedure. In the last two decades, this problem has been addressed by many researchers who have sought to develop combined (or integrated) models that can consider travelers’ choice on different stages simultaneously and give consistent results. In this paper, alternative formulations, including mathematical programming (MP) formulation and variational inequality (VI) formulations, are provided for a combined travel demand model that integrates trip generation, trip distribution, modal split, and traffic assignment using the random utility theory framework. Thus, the proposed alternative formulations not only allow a systematic and consistent treatment of travel choice over different dimensions but also have behavioral richness. Qualitative properties of the formulations are also given to ensure the existence and uniqueness of the solution. Particularly, the model is analyzed for a special but useful case where the probabilistic travel choices are assumed to be a hierarchical logit model. Furthermore, a self-adaptive Goldstein–Levitin–Polyak (GLP) projection algorithm is adopted for solving this special case.     

隔膜式电解槽生物膜阴极降解苯酚的过程及其条件的优化

以炼油废水中的主要污染物苯酚为目标污染物, 采用不同生物膜电极反应器对苯酚进行降解, 从而寻找出降解苯酚的最佳反应途径. 研究结果表明, 运用隔膜式电解槽生物膜阴极区域对苯酚废水进行处理, 其苯酚的去除效果虽然没有在生物膜阴极与阳极相混合的混合式反应器中处理效果好, 但在18 h内苯酚浓度降解到0, 并且其化学需氧量(COD)去除率最高, 在16 h内COD去除率达到80%. 对于隔膜式电解槽生物膜阴极区域的降解条件优化后发现, 电流设定为5 mA, 初始苯酚质量浓度低于200 mg/L, 温度为35 ℃时, 苯酚降解效果最佳.