准备多少货源平均收益最大

设某商品每年的需求量ξ(吨)是随机变量,其概率分布为已知.假设每销售一吨可获利润s元,但若年内销售不出,那么每吨将耗费保管费t元.对商店而言,若进货较多,那么若全卖出的话将获利较多,但卖不完的话将白白损失保管费,但若进货较少,保管费的损失则较小,但很可能白白丢失许多获利的机会,因此究竟备多少货最为合适呢?这就是本文所要讨论的问题.因为年需求量ξ是随机变量,从而年收益也是随机变量,为比较方案的好坏,我们考虑平均收益,即考虑年收益的数学期望.本文所讨论的问题是应组织多少货源才能使平均收益(收益的数学期望)为最大.本文分别就年…     

外卖食品安全问题的演化博弈分析

运用演化博弈论的方法对外卖商家之间,订餐平台监管部门和外卖商家之间相互作用时策略选择行为进行分析.结果表明:当外卖商家生产不合格的外卖收益大于生产合格外卖的收益、订餐平台监督部门对生产不合格外卖的商家处罚力度过轻或对外卖合格性的检测成本过高时,不合格外卖生产必然发生.要确保外卖商家生产合格外卖,就必须对生产不合格外卖的商家进行严惩,降低生产不合格外卖的预期收益.同时,要加强订餐平台建设,降低监管成本,保证监管部门严格执法.     

一个能够抗击Sybil攻击的电子商务协议

尽管基于对等网络模式(P2P)的电子商务系统获得了巨大的成功,但是由于没有集中式的控制机制,所以容易受到sybil攻击和白洗(whitewashing)攻击.每个商家在购买货物时,总是希望从信任度高的商家进货.但是一些恶意的商家,可以虚构多个身份,进行虚假交易,任意提高自己的信任度.提出一个崭新的交易协议来限制Sybil和白洗攻击的能力.我们把商家间的历史交易关系映射为一个有向图,把评定商家信任度的问题转化为有向图中的最短路径问题.通过理论分析和数据仿真来评价该协议的性能.     

带有二次订购和二次销售的报童问题

本文提出二次进货二次销售的报童模型 ,并分析了新模型与经典报童问题和带有反馈生产模型的最优订购量及收益关系 ,分析了模型的灵敏度 ,服务水平等 .     

基于消费者机会主义行为的退货担保服务策略

退货担保服务在提高普通消费者购买产品信心的同时,也可能被机会主义消费者所利用,损害商家的收益.文章探讨了市场上同时存在两类消费者(普通消费者和机会主义消费者)时商家的退货担保服务策略.经研究发现,相较于不提供退货担保服务,低价的退货担保服务能增加两类消费者的产品购买意愿;除商家制定的退货担保服务价格过低的情形外,提供退货担保服务的产品收益总是高于不提供退货担保的产品收益;除市场中机会主义消费者较多且产品体验价值较高的情形外,提供退货担保服务的产品价格总高于不提供退货担保服务的产品价格.此外,若商家针对不同类型消费者制定差异化的退货担保服务服务价格,将能够消除由消费者机会主义行为导致的负面影响.     

考虑在线评论的产品免费试用策略

商家提供产品免费试用,要求试用者对产品质量进行在线评论,消费者基于在线评论进行购买决策。免费试用者数量越多,在线评论数量越多,消费者对在线评论越信任。考虑在线评论和产品生产成本,研究商家的产品免费试用策略及其对利润的影响。研究发现,虽然商家承受免费试用的产品生产成本损失,但是免费试用产生的在线评论可以使商家更好地按照产品质量制定价格,因此当产品生产成本较低时,提供免费试用可以提高商家利润。产品生产成本提高,商家的最优免费试用数量减少。产品质量不确定性越大或失配距离单位成本越低,免费试用给商家带来的收益越高。     

基于微分博弈的电商平台与商家合作模式研究

在数字经济的背景下,电商行业的快速发展对社会进步起到重要推动作用。为了研究电商平台和商家之间的合作模式,同时考虑商品商誉以及时间连续性,本文构建了由电商平台和多个商家组成的微分博弈模型;运用哈密尔顿-雅可比-贝尔曼方程,分别讨论分散式决策模型、集中式决策模型以及Stackelberg主从博弈模型下的电商平台和商家关于努力程度、商品定价等最优决策。通过对三种决策模型下参与者的努力程度、商品商誉以及系统整体收益的分析对比和数值实验,可以发现：在集中式的完全合作模式下,电商平台和商家的努力程度最高,商品商誉以及系统整体收益最高;而在Stackelberg主从博弈模型下,电商平台分担商家部分成本,平台与商家之间的合作与竞争并存,因此商品商誉和系统整体收益较分散式决策模型有所增加。因此得出结论：相比于各方独自谋利的分散式决策模型,电商平台与商家进行部分或者深度合作,可为双方带来更高收益,有利于整个电商生态系统的长远发展。     

可替代产品库存模型的研究

市场上,很多产品之间可相互替代,商家为了获得的更多的利润,经常会用一种产品替代另一种产品.不仅如此.某种产品缺货时,也可以重新进货以满足顾客的需求.我们从销售商的角度,讨论这两个因素对库存策略的影响,建立了这类问题有两个产品的单周期的利润最大化模型,证明了目标函数是凹的和子模的,从而问题的解是存在的,给出了最优订货量(原始库存)的必要条件,讨论了各参数对库存的影响.通过比较,证明了商家采取替代策略和允许再订货可以提高利润并且可减少库存总量.     

博弈联盟模糊收益的分配

提出了联盟模糊收益合理分配的一种新方法.首先,在模糊收益α截集上定义了α合理分配集,分析了该分配集与模糊收益Shapley值的关系.接着,给出了模糊收益的α合理Shapley分配函数,对其性质进行了讨论.然后,构造了模糊合理Shapley分配,证明其连续性,得到了联盟模糊收益与模糊合理Shapley分配具有包含关系的结论.     

寻租行为下的网络餐饮服务食品安全监管主体的决策分析

为了解决网络餐饮服务食品安全监管问题,以监管中的寻租行为为切入点,分析寻租情境下平台与商家的决策顺序和策略集合,并假设相关变量及参数,进而建立双方的决策收益模型.采用数值仿真方法对影响双方决策的因素进行剖析,通过调整影响商家和平台决策参数的取值,总结降低商家与平台消极决策及收受贿赂行为的激励措施,以期为网络餐饮服务食品安全趋于有效监管提供参考.     

一体化生产企业进货决策研究

综合考虑一体化生产企业原料使用中存在的间接消耗和循环消耗情况、企业进货受到的多种约束条件的限制以及多种物资的批量折扣的存在,在建立企业物资需求模型、进行物资需求量计算的基础上,建立了一体化生产企业进货决策模型,进而提出了模型的两种可供选用的求解方法：分解法、调整法。算例求解结果正确合理。     

Reserve stock models: Deterioration and preventive replenishment

Reserve stocks are needed in a wide spectrum of industries from strategic oil reserves to tactical (machine buffer) reserves in manufacturing. One important aspect under-looked in research is the effect of deterioration, where a reserve stock, held for a long time, may be depleted gradually due to factors such as spoilage, evaporation, and leakage. We consider the common framework of a reserve stock that is utilized only when a supply interruption occurs. Supply outage occurs randomly and infrequently, and its duration is random. During the down time the reserve is depleted by demand, diverted from its main supply. We develop optimal stocking policies, for a reserve stock which deteriorates exponentially. These policies balance typical economic costs of ordering, holding, and shortage, as well as additional costs of deterioration and preventive measures. Our main results are showing that (i) deterioration significantly increases cost (up to 5%) and (ii) a preventive replenishment policy, with periodic restocking, can offset some of these additional costs. One side contribution is refining a classical reserve stock model (Hansmann, 1962).     

MRP performance effects due to forecast bias and demand uncertainty

The effects of forecast bias and demand uncertainty in a batch production environment are investigated using an integrated MRP planning and execution test bed. The use of inflated planned lead time and safety stock to compensate for forecast error is evaluated. Analysis is performed in terms of meeting both the MPS due dates and customer delivery requirements. Forecast bias and demand uncertainty are shown to affect MPS and delivery performance quite differently. Results also show that increasing either planned lead times or safety stock is effective in improving delivery performance. If demand uncertainty dominates completion time variability, the use of safety stock will achieve delivery objectives with less finished goods inventory.     

Pooling of spare parts between multiple users: How to share the benefits?

Companies that maintain capital goods (e.g., airplanes or power plants) often face high costs, both for holding spare parts and due to downtime of their technical systems. These costs can be reduced by pooling common spare parts between multiple companies in the same region, but managers may be unsure about how to share the resulting costs or benefits in a fair way that avoids free riders. To tackle this problem, we study several players, each facing a Poisson demand process for an expensive, low-usage item. They share a stock point that is controlled by a continuous-review base stock policy with full backordering under an optimal base stock level. Costs consist of penalty costs for backorders and holding costs for on-hand stock. We propose to allocate the total costs proportional to players’ demand rates. Our key result is that this cost allocation rule satisfies many appealing properties: it makes all separate participants and subgroups of participants better off, it stimulates growth of the pool, it can be easily implemented in practice, and it induces players to reveal their private information truthfully. To obtain these game theoretical results, we exploit novel structural properties of the cost function in our (S − 1, S) inventory model.     

水泥产品结构的综合智能优化及应用研究

根据水泥市场需求信息,运用自适应模糊推理系统对水泥产品结构需求进行系统建模,应用并行遗传算法对模型求解,得到了来年的最优水泥产品结构需求计划,为水泥企业的生产规划及其经济效益的提高提供了重要的参考价值.     

Setting Company Stock Levels

This paper addresses the problem of how much total stock is required at a stocking location, with reference to a small number of overall characteristics. A relationship defining stock cover to throughput, number of items, overall service level, lead time and re-order interval is derived. Its use is seen as a strategic tool, to investigate the costs and benefits of changing service levels or amalgamating stocking points etc. The restrictions on its applicability are given.     

An integrated approach to the one-dimensional cutting stock problem in coronary stent manufacturing

This paper presents a two-stage approach for pattern generation and cutting plan determination of the one-dimensional cutting stock problem. Calculation of the total number of patterns that will be cut and generation of the cutting patterns are performed in the first stage. On the other hand, the second stage determines the cutting plan. The proposed approach makes use of two separate integer linear programming models. One of these models is employed by the first stage to generate the cutting patterns through a heuristic procedure with the objective of minimizing trim loss. The cutting patterns obtained from Stage 1 are then fed into the second stage. In this stage, another integer linear programming model is solved to form a cutting plan. The objective of this model is to minimize a generalized total cost function consisting of material inputs, number of setups, labor hours and overdue time; subject to demand requirements, material availability, regular and overtime availability, and due date constraints. The study also demonstrates an implementation of the proposed approach in a coronary stent manufacturer. The case study focuses on the cutting phase of the manufacturing process followed by manual cleaning and quality control activities. The experiments show that the proposed approach is suitable to the conditions and requirements of the company.     

The Further Study of Safety Stock under Uncertain Environment

Corresponding to stochastic variable, it is a better choice to describe the market demand uncertainty of innovative products with fuzzy variable because no historical data is available. Traditionally, possibility measure is regarded as the parallel concept of probability measure. However, it is, in fact, the credibility measure that plays the role of probability measure! Based on the credibility theory, this paper studies how to evaluate the safety stock of enterprise given desired product availability when the node enterprise market demand of supply chain is described by Gauss fuzzy variable. Thereinafter, the authors discuss the impact of required product availability and demand uncertainty on safety stock, compare the correlative issues with stochastic demand, and get some useful results.     

Forecasting demand variation when there are stockouts

This paper addresses the common problem of forecasting demand when there are a large number of stockouts. The well-known single period stochastic inventory (or ‘newsboy’) problem provides the optimum, single period, stocking level for a product subject to stochastic demand. There are many situations where repetitive ‘newsboy’ solutions are implemented to guide stocking of repeat, but related, products, such as newspapers, magazines, or perishable groceries. Implementation of the ‘newsboy’ solution requires forecasts of the distribution of demand, although there are many plausible cost parameters that lead to optimum stocking policies where there is a high probability of a stockout. The company is, therefore, faced with the problem of attempting to forecast demand when a high percentage of the available sales data reflects the stock available for sale, rather than the true demand.A procedure has been developed¹ to improve estimates of the mean and variance of the distribution of demand when there are stockouts, but this procedure fails when the percentage of stockouts increases above 50%. A modified stockout adjustment procedure is presented in this paper, and it is shown that use of this new procedure can lead to greatly improved estimates of demand parameters, and greatly improved profitability, when there are a high percentage of stockouts.     

Measure of bullwhip effect in supply chains with autoregressive demand process

In supply chain management, one of the most critical problems which require a lot of effort to deal with is how to quantify and alleviate the impact of bullwhip effect – the phenomenon in which information on demand is distorted while moving upstream. Although it is well established that demand forecast, lead time, order batching, shortage gaming and price fluctuation are the main sources that lead to the bullwhip effect, the problem of quantifying bullwhip effect still remain unsolved in many situations due to the complex nature of the problem. In this research, a measure of bullwhip effect will be developed for a simple two-stage supply chain that includes only one retailer and one supplier in the environment where the retailer employs base stock policy for their inventory and demand forecast is performed through the first-order autoregressive model, AR(1). The effect of autoregressive coefficient and lead time on this measure will then be investigated.