考虑差别定价的闭环供应链协调应对突发事件研究

本文以一个新产品和再造品存在差别定价的零售商负责回收闭环供应链为研究对象,研究突发事件干扰下如何采用收益共享契约协调分散式决策闭环供应链的问题。首先,给出了一个可协调稳定环境下分散式决策闭环供应链的收益共享契约;其次,在突发事件同时干扰闭环供应链中新产品和再造品最大市场需求规模的情况下,分析了集中式决策闭环供应链的最优应对策略,并证实了原收益共享契约在突发事件干扰下会失效;最后,通过对原收益共享契约进行改进,解决了突发事件干扰下的分散式决策闭环供应链协调问题,且改进后的收益共享契约也能够协调稳定环境下的分散式决策闭环供应链。     

规模不经济下基于一致定价和促销努力的双渠道供应链协调策略

在制造商存在规模不经济环境下,分别针对集中决策模式和分散决策模式,建立了基于一致定价和促销努力的双渠道供应链协调策略模型,分析了规模不经济和服务负溢出效应对供应链运营决策的影响,得到了集中和分散决策下各企业最优运作策略和收益。研究指出,规模不经济的双渠道供应链在分散决策批发价契约下无法实现供应链协调;而分散决策网络渠道收益共享契约能够实现双渠道总收益等于集中决策模式下供应链收益,但无法保证各主体始终获得高于批发价合同下的收益;进一步,设计了带有固定补偿的网络渠道收益共享契约,通过对固定补偿值的有效设计,不仅可以保证双渠道总收益等于集中决策模式下供应链收益,且可以始终保证各主体收益不低于分散决策批发价契约下其所得收益,从而实现各主体利益双赢以及供应链的有效协调。     

信息不对称下多因素波动的应急数量弹性契约

考虑突发事件导致市场需求大幅波动、市场价格随机波动,构建生产成本信息不对称时应急供应链的数量弹性契约模型,寻找最优定价及订货策略;与完全信息情形对比,分析突发事件的信息共享及其对供应链最优决策的影响程度。研究发现,在生产成本信息不对称情形下,突发事件发生时,虽然零售商设计的数量弹性契约可以有效体现真实生产成本,但对供应链协调不起作用。同时,如果市场需求规模缩减,制造商表现出隐藏信息行为,可以促使供应链整体效益增加。最后通过算例验证了这些结论。     

模糊需求环境下的三级供应链协调机制研究

研究一个由供应商、分销商和零售商组成的三级供应链系统在模糊需求环境下的协调机制。需求函数中的参数视为三角模糊数，分析模糊环境下的分散决策和集中决策过程，给出收益共享契约机制下的决策模型。最后通过一个数值分析表明，在模糊需求环境下，收益共享契约机制同样可以实现供应链中各成员间的协调。     

基于共同配送的快递企业末端服务网点定价博弈研究

在末端共同配送背景下,以快递共配联盟为研究对象,建立了分散决策和集中决策的定价博弈模型。对分散决策情景考虑了固定支付、按件支付、收益共享、服务水平补偿、收益共享与成本共担五种不同的利润分配方法。在构建模型时,考虑了快递员提成比例、同行竞争、服务水平、宣传水平对需求和成本的影响,给出了快递企业与合作企业的最佳决策。最后,分析在不同模式下联盟的服务水平、价格、利润变化。结果显示,集中决策下联盟的总利润最高,分散决策下使用收益共享与成本共担模式最佳。     

模糊连续需求下供应链收益共享契约机制研究

研究一个由供应商和零售商组成的两级供应链系统在模糊连续需求环境下的运作过程。将市场需求视为三角模糊数,利用模糊截集理论分析模糊连续需求下的分散决策和集中决策过程,并给出收益共享契约机制下的决策模型。研究结果表明：在模糊连续需求环境下,零售商的订购量存在唯一最优解;供应链系统的“双重边际化”效应同样存在;收益共享契约机制可以实现供应链中成员问的协调。最后,通过数值例子对模型进行了比较分析。     

基于“进场费+收益共享”契约的供应链协调策略研究

在超市等自助零售环境下,影响产品需求的往往是产品的感知质量,而产品感知质量不仅取决于产品质量水平,还受货架空间展示量的影响。本文基于价格和感知质量依赖的需求函数,分别建立了一体化供应链集中决策模型以及考虑是否存在进场费的寄售契约下零售商主导的Stackelberg博弈模型,研究了制造商和零售商的产品定价和货架空间展示策略,并给出了进场费+收益共享的供应链协调策略。研究结果表明分散供应链环境下产品的最优零售价格并不总高于集中决策下产品的最优定价,也就是说提升感知质量在一定程度上可以缓解双重边际效应。另外,收取进场费的收益共享模式可以实现供应链的完美协调,这在理论上说明了进场费模式在一定的市场环境下是合理的。     

基于可回收应急物资共享配置的微分博弈模型

灾害救援阶段经常存在着应急物资的过度供给,导致恢复阶段应急物资回收困难和浪费严重.共享经济为解决应急物资回收信息不对称和过度供给提供了新思路.但是,共享平台回收应急物资面临合理分配成本-收益的难题.从灾后恢复期的应急物资回收视角,构建以应急物资供应方企业、共享数据平台和需求方企业为参与主体的无成本分担决策、集中决策和成本分担决策三种应急物资配置微分博弈模型.得到如下结论,需求方支付给供应方的资源使用费满足一定条件时,成本分担决策可以提高需求方的匹配努力度,实现帕累托改进.集中决策在应急物资配置过程中任意时刻满足整体理性和个体理性的一致性,促使应急物资共享量和整体利润均达到最优.无成本分担决策实现局部最优,加重应急产业链的双重边际效应.     

基于双论域模糊粗糙集的应急决策模型与方法

以突发危机事件应急决策为应用背景,讨论了双论域上模糊粗糙集的基本理论,建立了基于模糊相容关系的双论域模糊粗糙集模型. 在此基础上,把突发危机事件应急决策转化为一个具有模糊决策对象的双论域决策近似空间上的粗糙近似问题,构建了基于双论域模糊粗糙集的应急决策模型.首先在双论域近似空间中计算模糊决策对象的上(下)近似,进而结合经典非确定型决策的思想给出了突发危机事件应急决策的规则.同时,给出了模型的算法.该模型给出了一种在不完全信息环境下应急决策的方法,给出了在充分考虑决策者个人偏好信息基础上的决策置信度以及最优决策规则.该方法能够比较充分地符合应急决策信息不充分、资源有限以及时间紧迫的基本特征, 进而对突发危机事件应急决策提供科学的理论基础和现实的决策方法.最后,通过应用算例说明了模型的应用过程,结果验证了本文给出模型的有效性。     

线上结合线下的供应链动态服务与定价决策研究

本文研究由一个传统电商企业和线下实体零售商组成的线上结合线下的供应链系统。由于线下服务努力能同时增加线上和线下的销售量,于是传统电商纷纷开设线下实体店,或者与已有的实体店进行合作。这两种模式分别对应集中决策和分散决策模式,因此本文构建了线上结合线下的供应链动态模型并研究这两种决策模式下的最优服务和定价决策。结果表明:(1)当线下渠道偏好增加时,无论是集中决策下还是分散决策模式下,企业都应该提高线下价格而降低线上价格以获得最优利润,而在分散决策模式下,传统电商还应该提高其批发价格;(2)成本分担策略能够提高线下实体店对服务的投入,从而提高服务和商誉水平;(3)成本分担策略能使线下零售店和传统电商的利润水平都得到了提高,实现了帕累托改进;(4)当满足一定条件时,成本分担-收益分担机制能够实现供应链的协调。     

Integrating restoration and scheduling decisions for disrupted interdependent infrastructure systems

We consider the problem faced by managers of critical civil interdependent infrastructure systems of restoring essential public services after a non-routine event causes disruptions to these services. In order to restore the services, we must determine the set of components (or tasks) that will be temporarily installed or repaired, assign these tasks to work groups, and then determine the schedule of each work group to complete the tasks assigned to it. These restoration planning and scheduling decisions are often undertaken in an independent, sequential manner. We provide mathematical models and optimization algorithms that integrate the restoration and planning decisions and specifically account for the interdependencies between the infrastructure systems. The objective function of this problem provides a measure of how well the services are being restored over the horizon of the restoration plan, rather than just focusing on the performance of the systems after all restoration efforts are complete. We test our methods on realistic data representing infrastructure systems in New York City. Our computational results demonstrate that we can provide integrated restoration and scheduling plans of high quality with limited computational resources. We also discuss the benefits of integrating the restoration and scheduling decisions.     

Restoring infrastructure systems: An integrated network design and scheduling (INDS) problem

We consider the problem of restoring services provided by infrastructure systems after an extreme event disrupts them. This research proposes a novel integrated network design and scheduling problem that models these restoration efforts. In this problem, work groups must be allocated to build nodes and arcs into a network in order to maximize the cumulative weighted flow in the network over a horizon. We develop a novel heuristic dispatching rule that selects the next set of tasks to be processed by the work groups. We further propose families of valid inequalities for an integer programming formulation of the problem, one of which specifically links the network design and scheduling decisions. Our methods are tested on realistic data sets representing the infrastructure systems of New Hanover County, North Carolina in the United States and lower Manhattan in New York City. These results indicate that our methods can be used in both real-time restoration activities and long-term scenario planning activities. Our models are also applied to explore the effects on the restoration activities of aligning them with the goals of an emergency manager and to benchmark existing restoration procedures.     

城市CIS物理关联脆弱性的动态分析方法

本文以城市关键基础设施系统(Critical Infrastructure System, CIS)为研究对象,将关键基础设施之间组成的复杂物理网络划分为个体层面、中观层面和系统层面三种类型,从物理关联势差的角度分析了城市CIS内部物理关联机理。根据城市CIS物理关联特性,引入元胞自动机(Cellular Automata, CA),以一种物理资源为主导建立模型,采用“自底向上”的方法,从微观关键基础设施活动推出宏观城市CIS表现。选取元胞连通性、元胞正常状态变化率和传输效率作为脆弱性评估指标,估算不同时间点城市CIS脆弱性的动态变化,实现物理关联脆弱性的动态分析,并运用加权平均值作为一段时间内城市CIS脆弱值。最后,以S城市为例,对物理关联脆弱性动态分析方法的合理性和有效性进行验证,评估结果为城市CIS保护提供支持。     

Coordinating decentralized local schedulers in complex supply chain manufacturing

Motivated by scheduling challenges in back-end semiconductor manufacturing, we propose a framework to oversee and integrate local decentralized scheduling algorithms utilized in complex supply chain manufacturing networks. We fill the gap between higher-level production planning and lower-level scheduling by establishing short-term production targets and priority scores for each product at each step in the system. Given a target output schedule, target cycle times for each step, the process and product structure, and initial WIP status, short-term production targets for each product/step are set. These targets can be used to evaluate the system performance and guide decentralized schedulers to control the system so as to achieve desirable outputs in dynamic environments.     

零售商回收电子废弃物条件下的定价模型研究

以废旧手机为例,在分散决策和集中决策条件下建立了零售商单独回收的定价模型.然后,分别求得了在分散决策下的Stackelberg均衡解与集中决策时的最优决策,并作了对比分析.结果表明:集中决策下的系统利润优于分散决策下的系统利润.最后,通过数值验证了相关结论.     

考虑充电设施重入的电动汽车旅行商问题研究

出于减少环境危害和响应相关法规的考虑,物流企业开始逐步将运输车辆转变为电动汽车;而由于电动汽车的续航里程有限,对电动汽车的路径优化也将涉及充电设施。充电设施的“重入”是指电动汽车返回之前已经通过的充电设施进行充能的现象,它的存在需要改变经典旅行商问题模型中的“子回路约束”。本文聚焦于充电设施的“重入”,构建了一个无需预估充电设施重入次数上限的电动汽车旅行商问题模型,并通过引入路径可行性判别方法和增加充电设施选择与重复策略,设计了一种改进蚁群算法对问题进行求解。结果表明:与未考虑重入的模型相比,本文提出的考虑充电设施重入的模型能在电动汽车电池容量较低的情况下求出最优解,同时也能够使充电设施承担多次充电任务,从而在较少充电设施情况下依然能够得到可行的最优路径。     

Prescriptive analytics for FIFA World Cup lodging capacity planning

The FIFA World Cup, comprising sixty-four matches spanning an entire month, has, in recent years, been attended by about three million spectators of which over half a million are visitors requiring lodging. Planning lodging capacity for an event of this magnitude is necessary for host nations where pre-existing infrastructures are either inadequate or lacking. This paper develops an optimization analytics framework that sequentially employs two integer programming models for foreign spectator analysis and the consequent lodging requirements. The framework is applied to assess the preparedness of lodging infrastructure in Qatar for FIFA 2022.     

A united search particle swarm optimization algorithm for multiobjective scheduling problem

The performance of a scheduling system, in practice, is not evaluated to satisfy a single objective, but to obtain a trade-off schedule regarding multiple objectives. Therefore, in this research, I make use of multiple objective decision-making method, a global criterion approach, to develop a multi-objective scheduling problem model with different due-dates on parallel machines processes, in which consider three performance measures, namely minimum run time of every machine, earlierness time (no tardiness) and process time of every job, simultaneously. According to this special multi-objective scheduling problem, the method of reverse order drawing GATT will be proposed, at the same time, bring forward a united search particle swarm optimization algorithm (USPSOA) solves this multi-objective scheduling problem. The validity and adaptability of the USPSOA is investigated through experimental results.     

装配型企业订货量分配与订单排产联合决策研究

针对供应商交货数量不确定环境下,多品种小批量装配型制造企业因生产物料不配套造成生产计划不可行甚至客户订单拖期的问题,从企业运作整体出发,考虑订货量分配决策对订单生产和交货的影响,以最小化采购成本和最小化订单排产相关成本为优化目标,在允许零部件拖期交货且供应商提供拖期价格折扣条件下,建立订货量分配与订单排产联合优化模型。针对可行解空间巨大、传统数学规划方法难以求解的问题,从增强搜索性能角度出发,设计基于自定义邻域搜索算子的局部搜索机制和基于随机与种群重构变异机制的改进粒子群算法的模型求解策略。通过应用实例对本文模型和算法进行了有效性验证和灵敏度分析,结果表明,相比于传统的分散决策方案,本文模型能够有效降低整体成本水平,引入的改进机制能够显著提升算法搜索性能,为企业供应风险下的运营决策制定提供理论参考。     

New fuzzy models for time-cost trade-off problem

The time-cost trade-off problem is a specific type of the project scheduling problem which studies how to modify project activities so as to achieve the trade-off between the completion time and the project cost. In real projects, the trade-off between the project cost and the completion time, and the uncertainty of the environment are both considerable aspects for managers. In this paper, three new fuzzy time-cost trade-off models are proposed, in which credibility theory is applied to describe the uncertainty of activity duration times. A searching method by integrating fuzzy simulation and genetic algorithm is produced to search the quasi-optimal schedules under some decision-making criteria. The purpose of the paper is to reveal how to obtain the optimal balance of the completion time and the project cost in fuzzy environments.