Measuring and Achieving Equity in Multiperiod Emergency Material Allocation

Emergency material allocation is an important part of postdisaster emergency logistics that is significant for improving rescue effectiveness and reducing disaster losses. However, the traditional single‐period allocation model often causes local surpluses or shortages and high cost, and prevents the system from achieving an equitable or optimal multiperiod allocation. To achieve equitable allocation of emergency materials in the case of serious shortages relative to the demand by victims, this article introduces a multiperiod model for allocation of emergency materials to multiple affected locations (using an exponential utility function to reflect the disutility loss due to material shortfalls), and illustrates the relationship between equity of allocations and the cost of emergency response. Finally, numerical examples are presented to demonstrate both the feasibility and the usefulness of the proposed model for achieving multiperiod equitable allocation of emergency material among multiple disaster locations. The results indicate that the introduction of a nonlinear utility function to reflect the disutility of large shortfalls can make the material allocation fairer, and minimize large losses due to shortfalls. We found that achieving equity has a significant but not unreasonable impact on emergency costs. We also illustrate that using differing utility functions for different types of materials adds an important dimension of flexibility.     

国家级新区义务教育资源供需矛盾及消解路径——基于N市J区12345政务热线数据分析

成立国家级新区对迅速改善欠发达地区经济环境、改变落后的民生状态进而促进城市区域发展具有重要意义。国家级新区应努力推动社会公共服务体系与产业发展体系协同共进。义务教育资源是社会公共服务体系的重要组成部分，不容忽视。国家级新区在初创的关键时期需要打好义务教育资源均衡分配的基础，为后续义务教育资源的优化升级提供坚实保障。本文以N市J区为例，通过对12345政务热线服务平台的数据分析和对关键人物的访谈，探讨国家级新区初创期义务教育资源需求特征，同时发现实际存在着义务教育资源供不应求、供需脱节、配置失衡、提质升级乏力等供需矛盾，并依据新区初创阶段的实际需求，从制定规划、资金支持、供需互动、创新升级等方面进一步探讨国家级新区义务教育资源供需矛盾的消解路径。     

基于优先权拍卖的产能分配机制研究

本文考虑一个供应商和两个独立零售商构成的供应链系统。当供应商的产能受到约束时，零售商可能会竞争有限的产能。本文提出将“优先分配权”作为一个有价值的标的物进行拍卖，按照出价高低确定优先分配顺序。本文证明了优先权拍卖机制属于共同价值模型，并提出了两类拍卖机制：事先拍卖和事后拍卖。本文证明两类优先权拍卖机制均会促使零售商提交真实的需求作为订单量，并且满足收益等价定理。而就供应商期望利润而言，事后优先权拍卖机制要高于事先优先权拍卖机制。     

An omnibus two-sample test for ranked-set sampling data

We develop an omnibus two-sample test for ranked-set sampling (RSS) data. The test statistic is the conditional probability of seeing the observed sequence of ranks in the combined sample, given the observed sequences within the separate samples. We compare the test to existing tests under perfect rankings, finding that it can outperform existing tests in terms of power, particularly when the set size is large. The test does not maintain its level under imperfect rankings. However, one can create a permutation version of the test that is comparable in power to the basic test under perfect rankings and also maintains its level under imperfect rankings. Both tests extend naturally to judgment post-stratification, unbalanced RSS, and even RSS with multiple set sizes. Interestingly, the tests have no simple random sampling analog.     

企业资源配置战略与盈余持续性

盈余持续性是盈余质量的重要特征。较高的盈余持续性预示着企业的盈余质量较高,在一定程度上表明企业的经营状况平稳并具有良好的管理水平,有利于企业降低经营风险、提升公司价值。近年来,盈余持续性已经成为资本市场研究领域的一个热点问题。以我国A股市场2007—2017年非金融类上市公司为样本,对企业资源配置战略与盈余持续性之间的关系进行了实证研究。研究结果表明,经营主导型公司的盈余持续性要显著强于投资主导型公司;进一步区分具体的盈余构成后发现,经营主导型公司核心利润的持续性显著强于投资主导型公司,但其投资收益的持续性显著弱于投资主导型公司。上述结论表明,盈余及其构成的持续性均会受到公司资源配置战略的影响。相关研究结论既为公司资源配置战略影响盈余特征提供了经验证据,又对外部利益相关者透过战略本质看清会计信息的内在价值具有一定的启示作用。     

考虑进口配额的跨国供应商选择与订单分配模糊多目标优化决策

针对跨国供应商选择与订单分配问题,在考虑进口配额限制和需求不确定的情境下,构建了一个实现核心制造商利润最大化和供应商交货质量最大化的模糊多目标混合整数规划模型。该模型考虑汇率、关税等多个全球因素,采用一种交互式模糊多目标规划方法对模型进行求解,并应用一个算例进行验证。研究表明:1.存在进口配额限制时,制造商会优先考虑低成本高质量的海外供应商,达到配额限制后再选择本土供应商补充剩余订单;2.人民币汇率正向影响制造商海外采购。当人民币汇率上升时,制造商进口成本降低,其会将更多订单分配给海外供应商;3.关税负向影响制造商海外采购。当关税上升时,制造商会减少关税高的供应商的进口数量,选择替代供应商来满足其需求。由此获得如下管理启示:1,制造商企业在选择跨国供应商时,应重点关注本国的进口配额政策,使供应商多样化以减少针对单一供应商配额政策剧烈波动对制造商采购成本和企业利润的不利影响。2.汇率时刻都在变动,制造商企业应关注本国和供应商所在国的长期汇率政策以及短期突发事件对汇率的影响,及时调整订单分配决策。3.制造商企业在选择供应商时,需要对供应商所在国的短期和中长期关税政策进行综合评估。     

万物互联时代的“算法”崇拜与资源配置变革

随着万物互联时代的来临，人类资源配置将被各种人工智能“算法”①所取代。万物互联产生的数据将成为社会资源的重要形态，也是支撑人工智能“算法”的重要基础。数据资源的安全、所有权归属、开发利用效率以及保密等重要议题，将成为民族学、经济学、社会学和心理学等相关学科关注和研究的新热点。我国是一个统一的多民族国家，如何将丰富的民族多样化资源转化为支持万物互联资源网络协同优化配置人工智能“算法”的数据，需要从民族历史、文化、生物、信息处理技术等相关学科做深入的理论和实证研究。在万物互联时代，因资源配置方式与配置机制发生变革，经济学一般不再直接求解资源最优配置的策略集，更多是从理论和实证方面研究资源配置中人工智能“算法”的构造原理、构造条件与影响因素。万物互联时代，社会和谐秩序的构建，需要政府建立和维护万物互联网络的安全防护体系，并对资源配置中人工智能技术演变路径作规范和指引。     

Water cycle algorithm for solving the reliability-redundancy allocation problem with a choice of redundancy strategies

Abstract

This paper proposes a new mathematical model for the reliability-redundancy allocation problem (RRAP) with a choice of redundancy strategies. To maximize the reliability of a system, this model chooses the best redundancy strategy from among both active and standby ones for each subsystem. For those with a standby strategy, a continuous time Markov chain model is used to calculate the exact reliability values. In order to solve the proposed mixed-integer non-linear programing model, a powerful evolutionary algorithm, called water cycle algorithm (WCA), is developed and implemented on three famous benchmark problems. Finally, the results of different benchmark problems are compared with those previously reported to show the superiority of the proposed model and the efficiency of WCA.     

Dynamic optimal capital growth of diversified investment

We investigate the problem of dynamic optimal capital growth of diversified investment. A general framework that the trader maximize the expected log utility of long-term growth rate of initial wealth was developed. We show that the trader's fortune will exceed any fixed bound when the fraction is chosen less than critical value. But, if the fraction is larger than that value, ruin is almost sure. In order to maximize wealth, we should choose the optimal fraction at each trade. Empirical results with real financial data show the feasible allocation. The larger the fraction and hence the larger the chance of falling below the desired wealth growth path.     

Risk‐Cost‐Benefit Analysis for Transportation Corridors with Interval Uncertainties of Heterogeneous Data

Access management, which systematically limits opportunities for egress and ingress of vehicles to highway lanes, is critical to protect trillions of dollars of current investment in transportation. This article addresses allocating resources for access management with incomplete and partially relevant data on crash rates, travel speeds, and other factors. While access management can be effective to avoid crashes, reduce travel times, and increase route capacities, the literature suggests a need for performance metrics to guide investments in resource allocation across large corridor networks and several time horizons. In this article, we describe a quantitative decision model to support an access management program via risk‐cost‐benefit analysis under data uncertainties from diverse sources of data and expertise. The approach quantifies potential benefits, including safety improvement and travel time savings, and costs of access management through functional relationships of input parameters including crash rates, corridor access point densities, and traffic volumes. Parameter uncertainties, which vary across locales and experts, are addressed via numerical interval analyses. This approach is demonstrated at several geographic scales across 7,000 kilometers of highways in a geographic region and several subregions. The demonstration prioritizes route segments that would benefit from risk management, including (i) additional data or elicitation, (ii) right‐of‐way purchases, (iii) restriction or closing of access points, (iv) new alignments, (v) developer proffers, and (vi) etc. The approach ought to be of wide interest to analysts, planners, policymakers, and stakeholders who rely on heterogeneous data and expertise for risk management.