基于Poisson分布需求的两级零售系统最优订货策略

考虑由一个分销中心和N个零售商组成的两级分销库存系统．假设两级库存补充均采取周期订货策略，在每个零售商处的客户需求是随机的，且服从Poisson分布．当给定的某一货物缺货时，顾客愿意等待特别订货的概率是一确定的常数，在满足给定的客户服务水平的条件下，寻求该供应链总费用的最小化．对库存费用的计算进行了精确的推导，并且得到了最优的订货策略．最后给出了一个算例，根据所得到的公式由电子表格获得了两级最优库存水平．     

Understanding manager resistance to blockchain systems

Blockchain technology has received much attention in the media and there is an increasing interest amongst organizations within financial services due to the potential benefits. As blockchain-based systems are a nascent technology, the requirements of the technology need to be understood, to allow blockchain systems to be successfully integrated within financial service organizations. There are gaps in academic research in understanding how managers evaluate the value of a blockchain-based system. This study develops a model to explain manager resistance to implementing blockchain-based systems in financial services organizations. This research advances the theoretical understanding of managers’ perspectives on blockchain-based systems and models their resistance to blockchain technology.     

基于二阶段随机规划的城市医疗废弃物回收网络设计

城市医疗废弃物日益增加,且回收需求量受诸多因素的影响,难以准确预测,假定回收需求为确定值的医疗废弃物网络优化设计不能与实际需求相匹配。本文考虑了离散随机参数环境下,医疗回收网络设计中选址规划、分配计划及运输规划的协同优化问题,建立了以选址成本、运输成本最小为目标,设施与车辆能力限制为约束的二阶段随机规划模型。根据模型特点,设计了基于Benders decomposition的求解算法,同时,设计了一系列加速技术用于提高算法的求解效率。最后,以国内某城市医疗回收网络为背景设计算例,检验本文模型和求解策略的可行性和有效性。结果表明：相比确定性规划,随机规划的解能够节约总成本,结合一系列加速技术的Benders decomposition方法比CPLEX与纯的Benders decomposition更有优势。     

Sampling from spatial databases

This paper deals with techniques for obtaining random point samples from spatial databases. We seek random points from a continuous domain (usually ²) which satisfy a spatial predicate that is represented in the database as a collection of polygons. Several applications of spatial sampling (e.g. environmental monitoring, agronomy, forestry, etc) are described. Sampling problems are characterized in terms of two key parameters: coverage (selectivity), and expected stabbing number (overlap). We discuss two fundamental approaches to sampling with spatial predicates, depending on whether we sample first or evaluate the predicate first. The approaches are described in the context of both quadtrees and R-trees, detailing the sample first, acceptance/rejection tree, and partial area tree algorithms. A sequential algorithm, the one-pass spatial reservoir algorithm is also described. The relative performance of the various sampling algorithms is compared and choice of preferred algorithms is suggested. We conclude with a short discussion of possible extensions.     

Cybernetic Risk Analysis

The Pearl Harbor case study reveals that risk analysis failure may be caused by any of a number of factors. However, the most important variables are system load, gain, lead time, and lag time. The dynamics of such cybernetic systems analysis constitute an important aspect in this regard. Four different risk management strategies, or organization designs, have been proposed in this paper. Each has a unique combination of the imputed variables and each has a unique cause of surprise, risk analysis failure, and crisis.     

On the effectiveness of cognitive feedback from an interface agent

The objective of this study was to determine the impact of task information (TI) provided by an interface agent during the idea evaluation and integration step of the problem formulation stage of the problem solving process. The effectiveness assessment was based on solving diagnostic decision problems in the domain of complex industrial machinery. Ten domain experts participated in this study. Decision support was provided by a case-based reasoning system. Findings suggest that TI provided by the interface agent had no effect on the decision maker's performance, nor on the associated cognitive effort. However, a verbal protocol analysis revealed that the ten subjects used the interface agent to verify their decision processes. The results and their implications are discussed with respect to current findings in the area of decision support systems.     

Adaptive Build-up and Breakdown of Trust: An Agent Based Computational Approach

This article employs Agent-Based Computational Economics (ACE) to investigate whether, and under what conditions, trust is viable in markets. The emergence and breakdown of trust is modeled in a context of multiple buyers and suppliers. Agents develop trust in a partner as a function of observed loyalty. They select partners on the basis of their trust in the partner and potential profit, with adaptive weights. On the basis of realized profits, they adapt the weight they attach to trust relative to profitability, and their own trustworthiness, modeled as a threshold of defection. Trust and loyalty turn out to be viable under fairly general conditions.     

两阶段供应链中三种定价方式研究

本文考虑渠道一体化对品牌建设的作用,在一个制造商和两个零售商的两阶段供应链系统中,其中确定性的市场需求与产品的市场零售价格有关,通过分析以下三种定价方式下的最优定价和库存策略下供应链成员和系统的收益,1)商品市场零售价格由零售商各自决定,两零售商和制造商之间存在着竞争活动;2)商品市场零售价格由制造商统一制定;3)市场零售价格、转让价格和系统库存水平按渠道协调的最优原则确定,确定了同一产品品牌内部的市场竞争、定价控制权及转让价格对渠道性能及品牌自身造成的影响,并由此提出了分散决策系统中的一种激励机制.     

基于提前期的多阶通用件库存模型

针对单个企业内部应用通用件的环境,在假定一个多阶生产系统的基础上,对应用通用件的库存量水平及其成本进行了分析,建立了多阶通用件库存模型,提出通过对采用通用件和不采用通用件的成本差异的比较,来决策多阶生产系统中在哪一阶工序采用通用件,并求解出每一阶工序优化的基本库存水平。     

带有快速反应策略供应链系统的补偿策略研究

过长的订购提前期往往使得零售商订货决策感到困难. 快速反应策略能使零售商在获 得更多更准确的市场需求信息后,调整订购量而提高收益. 但是快速反应策略并不一定使供应 商的利润也提高. 有文章指出只有低的服务水平才能使两者利润同时提高,因而这种方法在工 业应用中是不一定可行的. 补偿策略是一种广泛应用的方法,能够提高产品的客户服务水平, 因而研究了补偿策略在快速反应供应链系统中的作用. 在某些条件下,在快速反应供应链系统 中,补偿策略能使零售商与供应商一方的收益不变或者提高,另一方的收益有所提高,即Pare2 to 提高. 还研究了引进补偿策略后,供应链系统的最优解及期望卖出量、期望缺货量和期望残 余量的变化情况.