存货管理模型的研究

在构建最佳采购批量模型的基础上,探讨了在不确定性因素条件下如何扩展最佳采购批量模型,主要有保险库存量的确定、订货点的确定和数量折扣条件下的订货量决策．     

Optimal inventory control policy and supply chain coordination problem with carbon footprint constraints

Carbon footprint constraints exert pressure on supply chains to reexamine decisions. In this paper, we consider carbon transfer cost and carbon holding cost in a supply chain. A multiperiod dynamic programming model with carbon footprint constraints is presented to investigate the impact of carbon transfer cost and carbon holding cost on inventory control policy as well as the supply chain coordination problem. A two‐control limit inventory control policy is proved to be optimal and a contract with wholesale price, subsidy, and fixed setup cost is verified analytically to coordinate the supply chain. Finally, a numerical study is conducted to reveal managerial insights. We find that when the supply chain is coordinated, the chain's profit is more sensitive to carbon transfer cost while inventory level is more sensitive to carbon holding cost. Additionally, because of the complexity of the coordinated contract, when it is not easy to coordinate the supply chain, it is better to keep the values of wholesale price, subsidy, and fixed setup cost below the corresponding values for the coordinated supply chain.     

前景理论对报童决策偏差的适用性

前景理论是不确定决策领域的基础理论, 而均值前景(mean prospect) 模型下的前景理论可以解释报童决策偏差现象. 为此, 通过改进均值前景模型, 构建不同产品下决策者参考点的计算方法, 提出了基于前景理论的库存决策模型, 并从理论上证明了前景理论与报童决策偏差之间的关系. 仿真结果显示, 不同产品中决策者的心理参考点、感知损失/获益区间存在显著差异, 部分产品中前景理论能够有效解释决策者的实际订购行为, 该结论与己有的研究成果一致.

     

基于免疫遗传算法的供应链库存协同优化研究

在全球经济一体化发展的大背景下,企业之间的竞争方式发生了本质上的改变,即已由原来单个企业之间的竞争变为企业间所在供应链之间的竞争。在这种竞争方式下,企业逐步向追求整个供应链利益的最大化转变。针对供应链整体协同运作来有效控制库存的问题,建立了多级库存供应链模型,运用改进的免疫遗传算法对所建的供应链多级库存模型进行优化求解;并以西部某实木家具公司的P1和P2产品为例,结合所建立的多级库存成本优化模型和相应的算法设计,运用Matlab数学仿真软件仿真求解。     

Optimal order policy in response to announced price increase for deteriorating items with limited special order quantity

When a supplier announces an impending price increase due to take effect at a certain time in the future, it is important for each retailer to decide whether to purchase additional stock to take advantage of the present lower price. This study explores the possible effects of price increases on a retailer's replenishment policy when the special order quantity is limited and the rate of deterioration of the goods is assumed to be constant. The two situations discussed in this study are as follows: (1) when the special order time coincides with the retailer's replenishment time and (2) when the special order time occurs during the retailer's sales period. By analysing the total cost savings between special and regular orders during the depletion time of the special order quantity, the optimal order policy for each situation can be determined. We provide several numerical examples to illustrate the theories in practice. Additionally, we conduct a sensitivity analysis on the optimal solution with respect to the main parameters.     

Pricing,manufacturing and inventory policies for raw material in a three-level supply chain

We studied a decentralised three-layer supply chain including a supplier, a producer and some retailers. All the retailers order their demands to the producer and the producer order his demands to the supplier. We assumed that the demand is price sensitive and shortage is not permitted. The goal of the paper is to optimise the total cost of the supply chain network by coordinating decision-making policy using Stackelberg–Nash equilibrium. The decision variables of our model are the supplier's price, the producer's price and the number of shipments received by the supplier and producer, respectively. To illustrate the applicability of the proposed model numerical examples are presented.     

Development of a particle number and particle mass vehicle emissions inventory for an urban fleet

Motor vehicles are major emitters of gaseous and particulate matter pollution in urban areas, and exposure to particulate matter pollution can have serious health effects, ranging from respiratory and cardiovascular disease to mortality. Motor vehicle tailpipe particle emissions span a broad size range from 0.003 to 10 μm, and are measured as different subsets of particle mass concentrations or particle number count. However, no comprehensive inventories currently exist in the international published literature covering this wide size range. This paper presents the first published comprehensive inventory of motor vehicle tailpipe particle emissions covering the full size range of particles emitted. The inventory was developed for urban South-East Queensland by combining two techniques from distinctly different disciplines, from aerosol science and transport modelling. A comprehensive set of particle emission factors were combined with transport modelling, and tailpipe particle emissions were quantified for particle number (ultrafine particles), PM₁, PM_2.5 and PM₁₀ for light and heavy duty vehicles and buses. A second aim of the paper involved using the data derived in this inventory for scenario analyses, to model the particle emission implications of different proportions of passengers travelling in light duty vehicles and buses in the study region, and to derive an estimate of fleet particle emissions in 2026. It was found that heavy duty vehicles (HDVs) in the study region were major emitters of particulate matter pollution, and although they contributed only around 6% of total regional vehicle kilometres travelled, they contributed more than 50% of the region's particle number (ultrafine particles) and PM₁ emissions. With the freight task in the region predicted to double over the next 20 years, this suggests that HDVs need to be a major focus of mitigation efforts. HDVs dominated particle number (ultrafine particles) and PM₁ emissions; and LDV PM_2.5 and PM₁₀ emissions. Buses contributed approximately 1–2% of regional particle emissions.     

A web-based decision support system for multi-criteria inventory classification using fuzzy AHP methodology

We propose an inventory classification system based on the fuzzy analytic hierarchy process (AHP), a commonly used tool for multi-criteria decision making problems. We integrate fuzzy concepts with real inventory data and design a decision support system assisting a sensible multi-criteria inventory classification. We report on a study conducted in a small electrical appliances company and validate the design of the proposed multi-criteria inventory classification system and its underlying fuzzy AHP model.     

3级网状随机性库存控制策略的仿真优化

研究了多制造商,多分销商和多零售商的3级网状随机性库存系统的(r,Q)库存控制策略问题.由于该系统具有顾客到达时间服从泊松分布,随机顾客需求量,随机顾客购买行为,随机订货时间和制造商生产容量有限制等特点,使得解析方法很难描述系统中的多种复杂随机因素并无法求解有效的库存控制策略.为此建立了以总成本最小为目标的数学模型,运用了基于仿真的优化方法,通过将仿真方法与粒子群优化算法相结合对问题进行求解.最后通过仿真实例与比较,验证了模型和基于仿真的粒子群优化方法的可行性和有效性.也表明了基于仿真的优化方法在供应链管理中的适用性.     

Dynamic supply chain design with inventory

In this paper, we deal with a facility location problem where we build new facilities or close down already existing facilities at two different distribution levels over a given time horizon. In addition, we allow to carry over stock in warehouses between consecutive periods. Our model intends to minimize the total costs, including transportation and inventory holding costs for products as well as fixed and operating costs for facilities.