租金费用和购买价格连续可变的在线租赁竞争策略分析

本文运用竞争分析方法研究了占线金融租赁决策问题,已往的研究都是基于租赁设备的租用费用和购买价格不变的情形给出最优投资策略,本文给出了当价格在有界范围内连续可变时的占线投资策略,并对有无利率两种情形分析进行了竞争策略分析,分别给出了其竞争比的上下界。     

具有概率分布在线租赁问题策略研究

在经济系统中,决策越来越呈现出在线性特征,传统优化方法在解决这类在线问题时,通常假设未来输入是一随机变量从而寻求概率意义上的最优决策。近年来,在优化领域兴起了一种新的研究方法——在线算法与竞争分析,为解决这类在线问题提供了新的视角,但传统的竞争分析方法有意规避概率分布假设。对于在线租赁决策问题,由于其输入结构简单且具有良好的统计性质,似乎忽略这些有用的信息而只运用标准的竞争比方法分析显然具有不足之处。在本文中,我们将其输入结构的概率分布引入纯竞争分析方法中,从而建立了具有概率情形的最优在线租赁模型,并得到了最优竞争策略及其竞争比。     

一类占线融资租赁问题的最优竞争策略与风险补偿模型

运用占线算法与竞争分析方法,研究了资产所有权在一定的租赁时间后转移给承租人的融资租赁问题的最优竞争策略与风险补偿模型。首先给出了该问题的最优离线解;然后,根据约定的租赁时限与购买价格及租赁费用的大小关系,分别给出了3种情形的占线策略及相应的竞争比分析;最后,在AL-BINALI提出的占线风险补偿分析框架下,给出了2种预期形式及相应最优占线收益策略。     

可退货在线租赁竞争分析及其风险回报模型

经典的在线租赁只考虑购买和租赁两种决策行为,当在线租赁方购买设备后,不允许退货。本文假设在线租赁方在选择购买设备后,如果觉得购买设备不划算,可以在任何时候花费一定的代价把设备退还给承租方。通过定义退货费用函数来刻画退货行为,本文提出了可退货在线租赁问题,它是经典在线租赁问题的扩展。利用传统的竞争分析方法设计了该问题的竞争策略,分析了策略的竞争性能,并证明该策略能达到竞争比下界(即是最优竞争策略)。同时,在风险回报竞争分析框架下,进一步讨论了上述问题,得到了给定预期和风险下收益最优的竞争策略。     

在线设备更新问题的竞争策略及其风险补偿模型

本文基于一种设备在线租赁的基础上,提出了在线设备更新问题。运用传统竞争比方法分别研究了两阶段设备更新问题在有无利率情形下的在线竞争策略,并建立了相应的风险补偿模型,从而在线投资者可以根据自己的风险容忍度和预期选择最优的更新策略。市场利率的引入使得在线设备更新模型更复杂但更贴近于现实中的设备更新问题。最后,通过具体实例进一步说明了市场利率下在线竞争比更小,而且竞争比关于市场利率递减;同时也说明了风险补偿模型中最优约束竞争比要小的多。因此,投资者若考虑到资金的收益及市场风险因素后将会采取更加谨慎稳健的投资策略。     

Online pickup and delivery problem with constrained capacity to minimize latency

The online pickup and delivery problem is motivated by the takeaway order delivery on crowdsourcing delivery platform, which is a newly emerged online to offline business model based on sharing economy. Considering the features of crowdsourcing delivery, an online pickup and delivery problem with constrained capacity is proposed, whose objective is to route a delivery man with constrained capacity to serve requests released over time so as to minimize the total latency. We consider online point-to-point requests with single pickup location where each request has to be picked up at the single pickup location and delivered to its destination, and each request become available at its release time, which is not known in advance. The lower bound of this problem for various capacities is proved. Two online algorithms WR and WI are presented, the competitive ratios on a half line and on general metric space are proved respectively. Further, a computational study is conducted to compare the performance of these two online algorithms on random instances of general metric space. The result shows algorithm WR performs better than WI in random cases but not in the worst case.

     

基于绩效比和合同约束的多阶段在线租赁

签订合同租赁是获得设备临时使用权的一种重要方式。设备承租方往往在不知道设备未来需求的情况下就需要确定合同的预租天数,这是一个在线决策问题。基于绩效比分析和线性分数规划方法,依次研究了合同约束下的单阶段和多阶段在线租赁决策问题,分别得到了最优的在线预租策略及其绩效比。借助于数值算例,进一步分析了日收益、租赁费、交易费和损失费等因素对最优预租策略及其绩效比的影响。研究结果可以为设备承租方确定预租天数提供一定的决策依据,也可以在确定租赁费、损失费等方面为设备出租方提供一定的理论指导。     

局内租赁问题的风险补偿模型及其竞争分析

将风险的概念引入局内租赁问题中,建立了该问题的风险补偿模型,并对存在和不存在 利率情况下的局内租赁问题作了分析. 和局内问题中传统的竞争比分析不同的是,竞争比分析 只反映局内策略与基准算法(局外最优算法) 的相对绩效,但这往往忽略了很多的有用信息,且 分析模型很不灵活. 然而在风险补偿模型中,投资者可以控制风险,根据自己不同的风险容忍 度和未来预期选择最优的租赁策略     

通胀市场下多设备租赁的在线策略分析

现实租赁市场中,企业同时租赁多台设备的现象大量存在,但经营者面临的最大难题是如何对这多台设备进行在线租赁的组合优化,从而降低决策成本,而通货膨胀又进一步增加了决策难度。本文运用在线算法和竞争分析法建立多设备投资的风险控制策略,并分析通胀对决策的影响。首先在Karp经典模型上给出通胀因素下多设备投资的最优在线和离线策略;接着建立设备租赁在连续可分情形下的最优风险控制模型,进一步结合实际投资中设备必须以离散整数租赁的特点,对CR策略进行调整和优化,得到近似的CRJ策略,使得策略更符合实际投资活动。最后给出具体实例分析,结果显示,当物价指数逐渐增大时,最优决策日期相应提前,对应最优策略的竞争比也逐渐增大,进一步说明物价指数因素和多设备投资因素的引入对投资者的决策有着重要的影响,为多设备在线租赁问题的研究提供了新的解决思路。     

Exact algorithms for scheduling programs with shared tasks

We study a scheduling problem where the jobs we have to perform are composed of one or more tasks. If two jobs sharing a non-empty subset of tasks are scheduled on the same machine, then these shared tasks have to be performed only once. This kind of problem is known in the literature under the names of VM-PACKING or PAGINATION. Our objective is to schedule a set of these objects on two parallel identical machines, with the aim of minimizing the makespan. This problem is NP-complete as an extension of the PARTITION problem. In this paper we present three exact algorithms with worst-case time-complexity guarantees, by exploring different branching techniques. Our first algorithm focuses on the relation between jobs sharing one or more symbols in common, whereas the two other algorithms branches on the shared symbols.

     

Greedy algorithms for the profit-aware social team formation problem

Motivated by applications in online labor markets, we study the problem of forming multiple teams of experts in a social network to accomplish multiple tasks that require different combinations of skills. Our goal is to maximize the total profit of tasks that are completed by these teams subject to the capacity constraints of the experts. We study both the offline and online settings of the problem. For the offline problem, we present a simple and practical algorithm that improves upon previous results in many situations. For the online problem, we design competitive deterministic and randomized online algorithms. These are complemented by some hardness results in both settings.

     

多阶段占线赁购问题与竞争分析

经典占线赁购决策是建立在设备使用寿命无限大的假设下进行竞争策略分析,是一种单阶段的占线决策问题。论文把设备使用寿命因素考虑进占线赁购问题,扩展单阶段占线赁购问题为多阶段占线赁购。给出了该问题的离线解;设计了等长赁购策略,证明该策略是唯一最优策略;给出了风险策略基本性质,为进一步研究多阶段占线赁购风险补偿模型奠定了基础。     

预测信息分享对制造商开通直销渠道的影响

研究了零售商预测信息分享对制造商渠道结构选择的影响.运用不完全信息动态博弈分别建立了单渠道和双渠道供应链决策模型,得到了贝叶斯均衡的渠道价格和各方最优期望利润.研究发现当零售商的需求预测精度比较低时,制造商应当开通直销渠道.零售商没有动机将预测信息与制造商分享.设计了一个信息分享补偿机制使得零售商能自愿分享其私有信息.在信息分享补偿机制下,虽然制造商为获取零售商预测信息付出了成本,但是依然有动机开通直销渠道.     

Competitive analysis for make-to-order scheduling with reliable lead time quotation

This paper makes extended studies on the discrete problem of online scheduling and reliable lead time quotation (discrete Q-SLTQ) introduced by Keskinocak et al. (Manag. Sci. 47(2):264–279, 2001). We first relax the assumption on revenue function from a linear decreasing function to any decreasing function. We present an online deterministic strategy which is optimal in competitiveness for concave revenue functions. The above results are further extended to the continuous Q-SLTQ model where orders are released at arbitrary time points. For the discrete Q-SLTQ problem, if orders are with nonuniform lengths, we prove the nonexistence of online strategies with bounded competitive ratios; otherwise if orders are with unit length but various weights, we present an optimal online strategy.     

How to reduce carbon emissions of small and medium enterprises (SMEs) by knowledge sharing in China

Abstract

Small and medium-sized enterprises are important components of the economy worldwide, and they are considered to be responsible for a large part of carbon emissions. However, because of the limitations in resource, knowledge and technical capabilities, most SMEs are confronting environmental issues such as the negative spillovers. The policy costs of an administrative order that is effective to promote emission reductions of large enterprises in China’s current economy could be high, and therefore, it is essential and crucial to establish a market-driven mechanism to help and encourage SMEs to make environmental improvement regarding the cap-and-trade system. In this context, new patterns of emission reduction would have profound impacts on knowledge management (KM) of SMEs, especially on knowledge sharing and knowledge transfer. In this paper, we adopt a micro-model to study the behaviors and carbon emissions of SMEs under different scenarios. We find that both trading and sharing of knowledge on carbon emission reduction are conducive to reducing emissions of SMEs in the context of cap-and-trade. Besides, the more the compensation is granted, the more manufacturing firms are willing to share knowledge with partners who have complementary knowledge. Subsidies or rewards on knowledge sharing can be helpful to reduce carbon emission, which may have important implications for public policy to solve the problem of carbon emission reduction of SMEs.     

Managing Risks in Multiple Online Auctions: An Options Approach*

The scenario of established business sellers utilizing online auction markets to reach consumers and sell new products is becoming increasingly common. We propose a class of risk management tools, loosely based on the concept of financial options that can be employed by such sellers. While conceptually similar to options in financial markets, we empirically demonstrate that option instruments within auction markets cannot be developed employing similar methodologies, because the fundamental tenets of extant option pricing models do not hold within online auction markets. We provide a framework to analyze the value proposition of options to potential sellers, option‐holder behavior implications on auction processes, and seller strategies to write and price options that maximize potential revenues. We then develop an approach that enables a seller to assess the demand for options under different option price and volume scenarios. We compare option prices derived from our approach with those derived from the Black‐Scholes model ( Black & Scholes, 1973 ) and discuss the implications of the price differences. Experiments based on actual auction data suggest that options can provide significant benefits under a variety of option‐holder behavioral patterns.     

考虑策略型消费者的在线零售商库存信息披露及联合定价、库存决策模型

在两期销售环境下,研究了面向策略型消费者的在线零售商库存信息披露及联合定价、库存决策问题。考虑在线零售商库存信息共享和隐藏两种库存披露策略,构建了在线零售商两期销售利润模型。通过分析消费者的购买行为,讨论了在具有策略型消费者的市场中,在线零售商应如何选择库存信息披露策略,以及如何制定最优定价和库存决策。在此基础上,分析了相关参数对在线零售商决策及利润的影响。研究结果表明,在线零售商的最优定价及库存决策受消费者估值折扣系数和第二期定价策略的影响。特别地,当在线零售商选择第一期缺货时,更倾向于共享其库存水平信息;当在线零售商选择第二期缺货或者两期均不缺货时,消费者估值折扣系数存在一个阈值,当低于该阈值时,在线零售商会选择隐藏库存水平信息,当高于该阈值时,在线零售商会选择共享库存水平信息。     

考虑订单类型的两台平行批处理机在线调度模型研究

探讨了两台平行批处理机的调度决策问题,着重考虑了订单具有不同加工类型、同一批次只能加工相同类型的订单以及机器批容量有限的调度情形。针对订单实时到达且需要立即决策是否接受的实际情景,运用在线理论构建了平行机批调度在线模型。证明了该问题的竞争比下界为2Bw/（1+√Bw）,其中B和w分别表示批容量和单个订单的最大完工收益。进而设计给出了收益阈值算法PT并证明其对于订单具有紧交货期限的情形竞争比为2（1+Bw）/（1+√Bw）;对于非紧交货期限的情形,证明了修正的PT算法具有竞争比为1+2（1+Bw）/（1+√Bw）。     

基于策略性竞争博弈的供应链信息共享策略

在供应链成员的市场信息以及成本非对称的情形下,讨论两个终端企业（一个自产自销,一个从上游批发产品）,在供应链中信息共享策略的方案,包括：信息优势企业如何根据市场需求情况确定是否信息共享（若是,则如何共享）;信息劣势企业如何根据对方透露出的市场信息来决策订货量;上游供应链如何决策批发价,从而控制整个供应链的博弈态势,使下游销售商在竞争中更为主动。经过研究发现,低市场类型时,自产自销商乐于共享信息,使竞争对手摄于低迷的市场状况从而降低订货量;在高市场类型且市场波动较小时自产自销商依然选择共享,在乐观的市场条件下表明自己的竞争优势,从而一定程度上威摄入侵者;而市场波动较大时,由于信息共享的额外收益不足以抵消信息共享需付出的额外成本,从而选择不共享信息。     

The comparison between trade-in and leasing of a product with technology innovations

Companies can adopt trade-in and/or leasing to shorten consumers׳ upgrade cycle and gain control over secondary markets. In this paper, we consider a monopolistic manufacturer who offers a technology product to a market consisting of heterogeneous consumers. We focus on an exogenous, stochastic innovation process that determines the availability of new technology and consequently, residual value of the current product. We derive the optimal pricing strategy of trade-in and leasing, respectively, examine its impact on the manufacturer׳s expected profit, and compare the performance of the two strategies. Trade-in protects the manufacturer against residual value risk and allows the flexibility of offering the option at different innovation states separately. Leasing, on the other hand, provides the manufacturer an opportunity to circumvent low new product prices and thus increases expected profit when product reuse profitability is high. The interplay between the two forces, product reuse profitability and new product price, determines the preference between trade-in and leasing. Our findings provide monopolistic manufacturers guidance on how to optimally employ the trade-in and leasing strategies.