行业的存货投资研究——基于经济“后危机”时代面板数据的实证分析

关于存货的研究在我国还并不成熟,前人大多是研究宏观经济与存货的波动关系,本文首先利用月度的采购经理人指数（PMI）从生产者角度分产成品存货和原材料存货进行H-P滤波分析,发现产成品与增长呈逆周期波动,原材料与增长呈顺周期波动;随后,细分行业分析增长与存货投资的波动关系,利用面板数据建立变系数模型,通过模型的系数可以观察行业存货的周期性,并通过P值的显著性划分出存货敏感型,产成品敏感型与原材料敏感型行业,同时结合存货的比重划分出高存货行业和敏感型行业,为行业的发展提供参考依据.     

供应链计划的模糊化解决VMI实施障碍的策略研究

供应链库存管理方法VMI(供应商管理用户库存)的实施遇到许多障碍,文中通过对障碍的分析结合理论和实践提出供应链计划的模糊化分解方法,希望寻求一种解决障碍的可行性方案。     

基于系统动力学的供应商管理库存仿真模型研究

由于供应商管理库存系统是高阶次、非线性、多重反馈的复杂大系统,用传统线性系统的理论和方法难以描述。文中在分析供应商管理库存模式的基础上,论述了基于供应商管理库存系统所涉及的关键因素,通过因果关系分析,构建了基于供应商管理库存策略的供应链动态仿真模型。通过调整本模型中的参数,可从灵敏度和瓶颈环节两个方面对模型进行分析和优化,使企业能在整个供应链管理战略实施前进行仿真实验,为企业制定库存决策提供辅助和参考。     

On the convexity of newsvendor games

This study considers a simple newsvendor situation that consists of n retailers, all selling the same item with common purchasing costs and common selling prices. Groups of retailers might increase their expected joint profit by inventory centralization, which means that they make a joint order to satisfy total future demand. The resulting newsvendor games are shown to have non-empty cores in the literature. This study investigates convexity of newsvendor games. We focus our analysis on the class of newsvendor games with independent symmetric unimodal demand distributions after providing several examples outside this class that are not convex. Several interesting subclasses, containing convex games only, are identified. Additionally, we illustrate that these results cannot be extended to all games in this class.     

Sustainable inventory management in blood banks considering health equity using a combined metaheuristic-based robust fuzzy stochastic programming

This study examines the challenges of healthcare systems toward sustainable inventory management of blood products. In this regard, three main goals are pursued; First, promoting social equity in providing medical services to various patients and reducing the risk to lives. Second, the optimal management of medical products in a way that minimizes economic costs. Third, optimal management of biological waste due to inventory corruption and reduction of greenhouse gas emissions caused by transportation, to the least environmental pollution. To achieve these purposes, a practical demand-driven multi-objective inventory model is presented by utilizing hybrid policies in an uncertain environment. In the proposed model, the demands are in two types, including elective and non-elective. These demands are classified according to their medical urgency, substitution allowance, and product freshness. A hybrid robust fuzzy stochastic programming approach is applied to capture real-world uncertainties. The proposed model is implemented for blood platelet. The solution is obtained using a combined metaheuristic technique established on genetic algorithms and simulated annealing according to global and local search paradigms. To create a proper perspective for decision-makers, sensitivity analysis is performed. Besides, the performance of the model is proved by the realization. The results show that the performance of the proposed RFSP model is better than the Nominal model. Also, it performs well in minimizing the overall system costs and environmental degradation, besides reducing shortage and wastage. It is also effective for taking steps toward equity in health and suggests a proper strategy for dealing with emergencies.     

Designing an integrated humanitarian logistics network for the preparedness and response phases under uncertainty

In the current paper, a model of possibilistic location-allocation is proposed for designing a multi-period bi-objective humanitarian logistics network that pursues a reduction in the total cost and maximizes the total network coverage. The model considers the inventory management of perishable relief items and the flow of affected and wounded people in pre-disaster and post-disaster phases, simultaneously. Moreover, wounded people are categorized according to the injury severity. The uncertainty associated with key parameters is also addressed. To handle the uncertainty, a fuzzy chance-constrained programming method originated in the Me measure is used. The purpose of this measure is to prevent the extreme attitudes of the decision maker by considering the combination of possibility and necessity measures and using the optimistic-pessimistic parameter. This paper presents a solution procedure derived from a fuzzy interactive programming approach and two meta-heuristic algorithms, imperialist competitive algorithm and invasive weed optimization, so as to solve the study model. As for the validation of the proposed model and solution procedures, a number of test problems have been generated. A real-life case study is also implemented to instantiate whether the proposed model is applicable or not.     

Dynamic inventory decisions for humanitarian aid materials considering budget limitations

In case of disaster, providing relief supplies to the affected people has vital importance. Governmental or non-governmental organizations (NGOs) prepare for disasters by purchasing and stockpiling these aid materials in appropriate quantities. They operate under a limited budget and this budget can either be used before the disaster for stocking decisions under uncertainty or it can be used after the disaster to satisfy the required demand at a higher cost when the uncertainty is resolved. If all the budget is used before the disaster, and if there is no disaster in a long term, there will be a high holding cost. On the other hand, if all the budget is reserved for use after the disaster, meeting the demand will be more costly or the demand may not be met within a certain period of time. Thus, NGOs need to decide how to allocate the budget for pre and post-disaster usage. In this system, the budget of NGOs may also change over time through donations or other incomes. In this point of view, NGOs need to make dynamic stock and budget allocation decisions, under the available budget at hand. In our study, we analyze the dynamic stocking decisions of NGOs using stochastic dynamic programming formulations under budget constraints. We develop infinite horizon stochastic dynamic programming models with and without budget considerations, and compare the results of these models via numerical analysis. Detailed numerical studies and results of the sensitivity analysis show the significance of budget considerations in inventory decisions and the effects of different parameters on the system results.