基于改进Shapley值法的新零售下供应链的利益分配策略

新零售的未来发展会呈现全渠道的发展趋势,将线上线下更深度的融合,创造更多的消费场景.而零售行业的竞争在很大程度上是供应链的竞争,集成更深的供应链,以持续优化的供应链来支持新零售的体验.然而作为虚拟的动态企业联盟,供应链在运作过程中常常会因链上各节点企业追求"自身利益最大化"而进行独立决策,导致整个供应链难以协调,因此建立激励相容利益分配机制、制定科学合理的分配策略成为确保新零售下供应链持续稳定发展的核心.针对新零售下供应链的收益分配问题,在传统Shapley值法的基础上,考虑风险承担、创新资源投入和业务执行度,引入综合修正因子,建立了改进Shapley值法来确定收益分配系数,进而实现新零售下供应链上各主体利益的合理分配,最后通过实际算例进行分析,验证了方法的合理性和有效性.     

服务大规模定制模式下的供应链调度优化

为了提升服务大规模定制(SMC)模式下供应链系统的运作柔性,应对客户较强的多样化需求特征,本文在对服务定制特征分析、服务阶段界定以及服务规模效应探讨的基础上,指出SCM模式下的供应链调度问题是一个典型的随机需求与随机资源约束的多目标动态优化问题。研究了SMC模式下供应链调度的优化目标与约束条件,建立了完整的随机多目标动态调度优化数学模型。基于SMC运作的特点,运用改进的蚁群算法对调度问题进行了求解。最后,通过实例分析了模型及算法的可行性、有效性及适用性。     

基于CRE的供应链渠道协作利润优化研究

为了实现供应链合作伙伴的双赢和多赢,在由一个制造商和两个批发商组成的供应链中,以制定最优共同补货周期策略为核心,制造商作为盟主指定共同补货周期和折扣率,批发商作为成员企业按共同补货同期的整数倍进行补货.制造商采用一致价格折扣的方式弥补批发商成本的增加.考虑到需求的可变性和是否实行共同补货周期策略,建立了制造商、批发商和整个供应链系统的利润优化模型并进行了模拟.结果表明共同补货周期策略可以实现多方收益的帕累托改进,供应链三方协作追求整体收益,可以实现"共赢".     

基于前摄性调度的电动汽车路径问题研究

针对车辆调度过程中资源不均衡的问题,利用需求的不确定性,将配送周期划分为初始配送阶段和补货阶段,建立多阶段电动汽车的两级车辆路径优化模型.根据需求的动态程度对配送区域进行划分,结合前摄性调度和反应性调度策略,提出了一种混合禁忌搜索算法(HTSA)来求解该模型.在真实的案例和多个基准评估算例上的实验结果表明:模型和算法的性能优于传统的启发式算法,具有一定的实用价值.     

MAS在连锁零售企业多级库存控制中的应用研究

高效的物流管理模式是连锁零售企业快速发展的基础和保障.在日益复杂的市场经济环境下,连锁零售企业必须解决库存量高,配送成本高,断货,配送无序,配送滞后等问题.针对这些问题,提出了一种在非等周期补货情况下,门店和配送中心库存水平的优化模型,解决了连锁零售业多级库存优化问题;建立了基于Multi-Agent-System的多级库存智能管理系统,解决了在连锁零售企业多级库存中普遍存在的配送无序、配送滞后等问题.     

基于多阶段模糊规模效应量化的TMC模式下供应链调度优化研究

旅游大规模定制(Tourism Mass Customization, TMC)模式实施的关键是通过对旅游供应链的调度优化处理旅游活动的“规模效应”与游客“个性化需求”之间的矛盾问题。运用经济学及模糊数学的理论方法分析并实现了TMC模式下存在的多阶段模糊规模效应量化处理。构建了引入规模效应量化的服务成本最小化、引入模糊时间窗的顾客满意度最大化及供应链协同度最大化为优化目标的TMC模式下多目标供应链调度优化模型。最后,通过蚁群算法实现TMC模式下多调度优化目标的求解并对优化效果进行对比研究。研究结果表明,TMC模式下供应链调度中旅游活动存在多阶段模糊规模效应并且可以量化处理;TMC模式中的规模效应具有合理的区间范围,旅游企业应注重规模效应与其他目标的均衡;蚂蚁算法在求解TMC模式下多目标优化问题方面不仅收敛速度快,而且通过对多调度目标优化效果的对比检验表明,性能稳健优良。     

一类多对多物流系统的运送频率选择优化问题研究

多供应商多客户物流系统的周期运送库存决策问题是一个非常复杂的问题,但它在供应链管理中又极其重要.本文主要考虑一个由多个供应商、一个联运中心和多个客户组成的三级物流系统的运送频率选择优化问题.假定两级库存均采用周期补货策略,且补货周期满足二次幂(POT)策略,每个客户处的产品需求为确定性需求.假设给定一套可行频率的情况下,选择使整个系统总的长期平均成本最小化的联运中心的补货策略和联运中心到各客户的配送策略.分为单频率配送和多频率配送两种情况分别建立了数学模型,并设计了相应的近似算法——基于支配性的邻域搜索启发式算法和基于饱和性的邻域搜索启发式算法.计算试验显示,本文所设计的近似算法对于求解多对多配送这样的大型组合优化问题是有效的.     

安全因子优化与协调模型研究

在需求和供应都不确定的情形下 ,通过模型研究对两阶供应链的安全因子优化与协调作了一些有益的探讨 .本文引入了有效库存水平的概念 ,以反映上游缺货对下游库存的影响 ,在基准库存水平补货模式下构造了的供需双方的库存模型 ,且对安全因子进行整体优化以降低供应链的库存成本 .     

基于期权契约的供应链协调研究

供应链协调与优化一直都是供应链管理的核心议题之一.为分析供应链竞合背景下的供应链协调问题,验证期权契约对供应链的协调效果,文章在分析供应链基本运作的基础上,利用优化理论和方法构建了无契约协调时供应链的基准模型和期权契约下的供应链模型,通过有无契约时供应链及供应链成员利润的对比,分析说明期权契约的协调效果,通过不同决策模式下供应链及供应链成员利润分析,给出期权契约完全协调供应链的条件.在此基础上,进一步引入供应商间和零售商间的跨链补货,验证跨链补货策略对于提高供应链成员利润的有效性.     

VMI条件下具有复合二项随机需求的销售商库存策略研究

考虑一个典型的单一产品的二级供应链系统:单供应商对单销售商,假定系统中销售商的需求分布为复合二项分布,未满足的需求机会损失;补货间隔时间为一随机变量.本文采用概率方法对销售商的需求分布、期望缺货、期望库存周期及库存的稳定性分布进行研究的基础上,构建了使单位时间内销售商的期望库存成本费用最小的库存模型,由此模型便可确定VMI模式下供应商对销售商的库存补货参数s和S,并且给出了在补货响应时间为泊松分布的情况下模型的求解算法,还给出了及时补货响应情况下的5个算例.为补货策略的实施提供了一种简单易于控制的思路和方法.     

Soft computing optimization methods applied to logistic processes

This paper discusses the methodologies that can be used to optimize a logistic process of a supply chain described as a scheduling problem. First, a model of the system based on a real-world example is presented. Then, a new objective function called Global Expected Lateness is proposed, in order to describe multiple optimization criteria. Finally, three different optimization methodologies are proposed: a classical dispatching rule, and two soft computing techniques, Genetic Algorithms (GA) and Ant Colony Optimization (ACO). These methodologies are compared to the dispatching policy in the real-world example. The results show that dispatching heuristics are outperformed by the GA and ACO meta-heuristics. Further, it is shown that GA and ACO provide statistically identical scheduling solutions and from the optimization performance point of view, it is equivalent to use any of the meta-heuristics.     

一种特殊的冲击型负荷模型及其供应链可靠度研究

基于一种特殊的单次冲击型负荷模型,对供应链系统受到冲击源N(t)为强度λ的poisson流冲击时的可靠性进行了研究.当冲击间隔小于常数δ时供应链失效,给出了供应链的可靠度函数及数字特征.研究表明可以通过预测该特殊冲击型负荷模型下供应链的期望寿命,做好应急物流保障.     

考虑双边服务水平的网购服务供应链协调契约

本文考虑了由单个网络商店和单个第三方物流企业(TPL)所构成的二级网购服务供应链,在双方服务水平同时影响市场需求的情况下,研究了网购服务供应链的服务质量协调问题。通过对比分散式和集中式供应链中各方的均衡决策,指出传统价格契约的不足,提出采用收益共享契约对供应链进行协调,并分析了该契约实现供应链协调的条件和局限。研究结果表明:收益共享契约能激励双方提高服务水平、实现供应链协调;协调契约实施前后各方的基本服务水平对各自的收益和服务决策均有正向影响,且相应的影响在协调契约下更明显。此外,研究还指出供应链系统可能会因TPL服务能力不足发生服务拥塞,使得系统运营效率降低。最后,通过算例验证了收益共享契约的有效性,并对主要参数的灵敏度进行了分析。     

Scheduling coordination problems in supply chain planning

Scheduling algorithms and their role in supply chain planning are topics that have been discussed in scheduling literature for many years. Based on examples and experience with commercial supply chain planning software, this paper presents background information about production planning and scheduling functionality in commercial supply chain planning software and interesting scheduling coordination problems in supply chain planning for researchers. We first provide an overview of different planning activities in supply chain planning, while taking into consideration existing functionalities that are available in commercial supply chain planning software. As a second step, we show three scheduling coordination problems in supply chain planning, namely the integration of production planning and production scheduling, the integration of sales order confirmation and production scheduling and the integration of VMI planning and production scheduling. We conclude this paper with a detailed discussion of an implementation of a supply chain planning solution at the tissue producer SCA Hygiene in Sweden. This paper expresses the authors opinion and does not represent an official statement from SAP.     

考虑释放时间的单机JIT调度问题

本文主要研究二级供应链中的生产-库存-直接配送协同调度问题,其中存在一个制造商和多个零售商, 制造商根据订单进行生产, 然后将产品配送给零售商。该类问题可以抽象为考虑释放时间的单机JIT调度问题。借助于禁忌搜索算法, 本文提出了求解问题的CTA-TS算法, 并通过大量的实验数据与已有算法进行比较,说明了本文提出算法的有效性。     

Distributed supply chain management using ant colony optimization

Successful supply chain management requires a cooperative integration between all the partners in the network. At the operational level, the partners individual behavior should be optimal and therefore their activities have to be planned using sophisticated optimization tools. However, these tools should take into account the planning of the remaining partners, through the exchange of information, in order to allow some kind of cooperation between the elements of the chain. This paper introduces a new supply chain management technique, based on modeling a generic supply chain with suppliers, logistics and distributers, as a distributed optimization problem. The different operational activities are solved by the optimization meta-heuristic called ant colony optimization, which allows the exchange of information between different optimization problems by means of a pheromone matrix. The simulation results show that the new methodology is more efficient than a simple decentralized methodology for different instances of a supply chain.     

Minimizing customer order lead-time in a two-stage assembly supply chain

Coordination across different process stages of the supply chain is becoming more common as the information needed for this coordination is easier to obtain and share. With the availability of this information, managers are beginning to recognize that there can be benefits to scheduling processes in a coordinated fashion. Thus, finding good schedules for the entire supply chain has added importance to today’s managers. Coordination of the material as it moves from one stage to the next should lead to improved customer order lead-time performance for the whole chain and thus better customer service overall. We look at a two-stage assembly supply chain with the objective of minimizing the average customer order lead-time. Minimizing lead-time is becoming increasingly important as customers demand quicker response. But beyond this better customer service objective, minimizing lead-time is consistent with keeping inventory costs low. We introduce a number of properties of optimal solutions, results for special problem cases, and a series of lower bounds. We also provide a number of intuitive heuristics for coordinated supply chain scheduling and test them to determine their effectiveness.     

App开发者质量投资和定价策略研究

本文考虑了由两个App开发者和一个下载平台商所构成的二级App供应链,在开发者间存在价格竞争和质量竞争的情况下,区分开发者竞争、开发者合作、供应链集中决策以及混合竞争四种不同的情景,建立了开发者质量投资和定价决策模型,分析了四种情景下开发者的均衡策略,并通过数值仿真进一步探讨了价格竞争程度和质量竞争程度对不同情境下均衡结果的影响。研究表明,高能力开发者的最优质量投资水平以及最优App价格均高于低能力开发者;价格竞争程度和质量竞争程度对非合作情形下的最优策略影响显著,对合作情形下的最优策略影响不显著;此外,App供应链总利润的高低取决于开发者与平台商之间合作的紧密程度。