A Bayesian approach to service level performance monitoring in supplier,provider relationships

Techniques are presented for monitoring the performance of a delivery service. The techniques were developed from the practical need to support two parties: a virtual retailer that out-sources the home delivery of its goods and the logistics business that provides its courier service. The techniques are relevant to contractual negotiations and performance monitoring. A graphical tool for hypothesis testing is presented as an aid to contract negotiation and a dynamic model is developed to track performance over time for operational management. The approach is based upon the beta-binomial distribution, within a Bayesian decision context.     

Advanced routing for city logistics service providers based on time-dependent travel times

Increasing traffic demand, recurring congestion and sophisticated e-commerce business models lead to enormous challenges for routing in city logistics. We introduce a planning system for city logistics service providers, which faces those challenges by more realistic vehicle routing considering time-dependent travel times. Time-dependent travel times arise from telematics-based traffic data collection city-wide. Well-known heuristics for the Traveling Salesman Problem and for the Vehicle Routing Problem are adapted to time-dependent planning data. Computational experiments allow for insights into the efficiency of individual heuristics, their adaptability to time-dependent planning data sets, and the quality and structure of resulting delivery tours.     

考虑平台竞争的众包物流社会配送服务最优定价策略

基于互联网的众包物流服务平台共享社会闲置人力资源,为电子商务O2O提供最后一公里配送服务。通过配送服务的动态定价来调控众包物流的社会配送供应能力,成为优化众包物流平台运营的重要手段。在众包物流平台激烈的竞争环境下,考虑到众包物流社会化配送供应能力的不确定性,采用动态优化理论,建立平台价格竞争下众包物流社会配送服务最优定价模型。运用汉密尔顿函数求解社会配送服务最优价格,研究众包物流社会配送服务供应能力随着价格变化的规律,进一步,分析众包物流平台竞争对最优价格变化规律的影响。数值仿真结果表明,众包物流社会配送服务价格增长率随着平台竞争的加剧而增加,可以有效调控众包物流服务的供应与需求平衡,优化众包物流平台的期望收益。     

基于体系工程与物流均衡的C2M服务制造物流体系结构模型

C2M服务制造是基于以顾客为中心的C2M(Customer to Manufacture)商业模式,是在服务型制造及生产性服务业为基础上而形成的一种新型产业模式。C2M服务制造要求构建合理的物流体系,而构建物流体系结构已经成为该研究的关键基础。本文基于体系工程和物流均衡理论,通过建立物流体系以解决C(客户)端与M(制造)端的短链式互联问题,在分析C2M服务制造物流体系特征和资源要素的基础上,给出了C2M服务制造物流体系的概念模型和结构模型,并运用价值函数分析体系状态是否优化,从而达到C端与M端快速互联的目标,进而解决了物流体系结构模型在C2M服务制造物流体系构建中的应用问题。     

A new VRPPD model and a hybrid heuristic solution approach for e-tailing

We analyze a business model for e-supermarkets to enable multi-product sourcing capacity through co-opetition (collaborative competition). The logistics aspect of our approach is to design and execute a network system where “premium” goods are acquired from vendors at multiple locations in the supply network and delivered to customers. Our specific goals are to: (i) investigate the role of premium product offerings in creating critical mass and profit; (ii) develop a model for the multiple-pickup single-delivery vehicle routing problem in the presence of multiple vendors; and (iii) propose a hybrid solution approach. To solve the problem introduced in this paper, we develop a hybrid metaheuristic approach that uses a Genetic Algorithm for vendor selection and allocation, and a modified savings algorithm for the capacitated VRP with multiple pickup, single delivery and time windows (CVRPMPDTW). The proposed Genetic Algorithm guides the search for optimal vendor pickup location decisions, and for each generated solution in the genetic population, a corresponding CVRPMPDTW is solved using the savings algorithm. We validate our solution approach against published VRPTW solutions and also test our algorithm with Solomon instances modified for CVRPMPDTW.     

基于即时配送和收益激励的众包物流运力调度研究

基于参与众包物流配送模式的人员闲散、积极性不高,以及客户对即时配送要求并非完全刚性的特征,引入模糊时间窗,将客户满意度量化为众包物流配送人员到达客户位置时刻的模糊隶属度函数。在一定客户满意度下,以最大化众包物流配送人员收益为目标,构建了基于即时配送和收益激励的众包物流运力调度问题模型,考虑到机会、逾时、超载惩罚成本,利用带有动态权重的粒子群算法,通过算例验证分析,结果表明该模型在保证客户满意度和提高众包物流配送人员积极性方面具有可行性和有效性。     

基于灰色规划理论的综合物流服务中心优化研究

随着国民经济的进一步发展,物流作为承载经济交易枢纽的关键环节对经济发展起着重要的促进作用,综合物流中心作为物流行业统筹规划的重要组成部分对物流效率的提高具有深远的影响.当前综合物流中心主要存在结构不合理,市场导向性差等弊端.本文主要利用灰色规划理论结合物流收益值的获取、预测等过程对综合物流中心进行了优化研究.结果表明,...     

A multiblock PLS‐based algorithm applied to a causal model in marketing

A modern approach to logistics allows it to be understood and used for its capacity to generate value, because value is managerially important as a strategic objective for any firm. In the present work a particular view of this approach is offered by providing a structural model where logistics service quality and sacrifices contribute to the formation of logistics value, but where service quality is also an important determinant of satisfaction. This combined approach, tested with multiblock partial least‐sqaures path modelling, in the particular setting of a business‐to‐business encounter, provides empirical support for a chain of effects between service quality–logistics value–satisfaction–loyalty without underestimating the important effect of service quality on satisfaction and satisfaction on loyalty in industrial settings. This proposed conceptual model of the relationship between customer loyalty and the various contributing factors to that loyalty is the main contribution in this paper. Copyright © 2012 John Wiley & Sons, Ltd.     

Optimal trading and shipping of agricultural commodities

We develop and implement a model for a profit maximizing firm that provides an intermediation service between commodity producers and commodity end-users. We are motivated by the grain intermediation business at Los Grobo—one of the largest commodity-trading firms in South America. Producers and end-users are distributed over a realistic spatial network, and trade with the firm through contracts for delivery of grain during the marketing season. The firm owns spatially distributed storage facilities, and begins the marketing season with a portfolio of prearranged purchase and sale contracts with upstream and downstream counterparts. The firm aims to maximize profits while satisfying all previous commitments, possibly through the execution of new transactions. Under realistic constraints for capacities, network structure and shipping costs, we identify the optimal trading, storing and shipping policy for the firm as the solution of a profit-maximizing optimization problem, encoded as a minimum cost flow problem in a time-expanded network that captures both geography and time. We perform extensive numerical examples and show significant efficiency gains derived from the joint planning of logistics and trading.     

Customer acceptance mechanisms for home deliveries in metropolitan areas

Efficient and reliable home delivery is crucial for the economic success of online retailers. This is especially challenging for attended home deliveries in metropolitan areas where logistics service providers face congested traffic networks and customers expect deliveries in tight delivery time windows. Our goal is to develop and compare strategies that maximize the profits of a logistics service provider by accepting as many delivery requests as possible, while assessing the potential impact of a request on the service quality of a delivery tour. Several acceptance mechanisms are introduced, differing in the amount of travel time information that is considered in the decision of whether a delivery request can be accommodated or not. A real-world inspired simulation framework is used for comparison of acceptance mechanisms with regard to profits and service quality. Computational experiments utilizing this simulation framework investigate the effectiveness of acceptance mechanisms and help identify when more advanced travel time information may be worth the additional data collection and computational efforts.     

Coordination of production and interstage batch delivery with outsourced distribution

In this paper, we consider coordinated production and interstage batch delivery scheduling problems, where a third-party logistics provider (3PP) delivers semi-finished products in batches from one production location to another production location belonging to the same manufacturer. A batch cannot be delivered until all jobs of the batch are completed at the upstream stage. The 3PP is required to deliver each product within a time T from its release at the upstream stage. We consider two transportation modes: regular transportation, for which delivery departure times are fixed at the beginning, and express transportation, for which delivery departure times are flexible. We analyze the problems faced by the 3PP when either the manufacturer dominates or the 3PP dominates. In this context, we investigate the complexity of several problems, providing polynomiality and NP-completeness results.     

考虑路径风险的需求不确定应急物流定位-路径问题

针对自然灾害对路网造成的破坏性和受灾点物资需求量的不确定性,综合考虑应急物流路径风险和物资分配的时间公平性,将路径风险定量化为路径通行能力风险、路径损毁风险和路径复杂性,基于鲁棒优化理论,以最小化车辆最长配送时间和应急物流系统总成本为目标,建立了双目标多物资定位-路径优化模型,采用遗传算法对其求解,以汶川地震应急救援相关数据为例进行了数据仿真实验。实验结果的对比分析表明:在考虑路径风险下,随着控制系数的增加,系统总成本和最长配送时间目标值均呈现增大的趋势;受灾点的物资需求扰动越大,构建应急物流系统的总成本越高。算例结果也验证了鲁棒优化方法在处理不确定需求方面的有效性,为解决自然灾害后应急设施点的开设和救援物资的安全及时准确配送提供了有效的方法。     

Machine scheduling with deliveries to multiple customer locations

One important issue in production and logistics management is the coordination of activities between production and delivery. In this paper, we develop a single-machine scheduling model that incorporates routing decisions of a delivery vehicle which serves customers at different locations. The objective is to minimize the sum of job arrival times. The problem is NP-hard in the strong sense in general. We develop a polynomial time algorithm for the case when the number of customers is fixed. More efficient algorithms are developed for several special cases of the problem. In particular, an algorithm is developed for the single-customer case with a complexity lower than the existing ones.     

考虑退货不确定性的多层次多站点逆向物流网络选址优化研究

在退货量不确定情况下,为追求电商企业逆向物流网络成本最小化,建立了多层次多站点的混合整数规划模型。将目标区域进行网格化处理,通过球上距离公式计算相邻备选站点、不同层次备选点间的运输距离,使用蒙特卡罗法模拟退货量,并设计了双染色体编码的遗传算法进行求解。算例验证了模型算法的可行性,并且得出了逆向物流网络成本最小时,快递站点和退货处理中心的选址,快递站点的选址与退货量大小存在对应关系,研究客户退货量会使物流网络选址得到优化。     

基于仓单质押融资的物流企业与银行的演化博弈分析

物流企业与银行之间的良好合作关系是物流金融业务继续发展的前提和基础。以仓单质押融资业务为例,运用演化博弈理论对物流企业与银行之间的监督包庇问题进行了分析,构建复制动态方程和运用动态相位图分析群体策略的演化过程及结果,为建立良好的合作关系提供理论依据。分析结果表明:该动态系统的演化方向受到博弈支付矩阵以及系统的初始状态的影响。银行监督成本、银行的收益损失、物流企业的包庇成本和物流企业的罚金是影响演化结果的关键性因素。通过外部力量的加入,可促使系统演化至(不包庇,不监督)这一期望演化稳定策略。     

以商圈为中心的O2O动态外卖配送路径优化模型与算法

针对线上到线下(Online to Offline,O2O) 外卖路径优化问题,综合考虑其动态配送需求、货物区分等特点以及时间窗、载货量等约束条件,将商圈看作配送中心,将快递员数量与快递员总行驶时间作为最小化目标,提出了以商圈为中心的O2O动态外卖配送路径优化模型。采用周期性处理新订单的方法将相应的快递员路径的动态调整问题转化为一系列静态TSP子问题,设计了一种分阶段启发式实时配送路径优化算法框架,并给出了一个具体算法和一个数值计算实例。在VRP通用算例的基础上,以商圈为中心生成测试算例,对本文算法进行仿真实验,并与其他算法比较。结果表明：本文算法能充分利用新订单附近的快递员进行配送,并优化其配送路径,有效减少了快递员数量与快递员总行驶时间。     

应急物流网络优化决策模型研究

应急物流环境的动态性与复杂性决定了应急物流网络应具有高度敏捷性与柔性.将应急物流系统的运行划分为四个不同阶段,分析了不同阶段应急物流所追求的目标重要性的变化趋势,引入罚函数系数来均衡不同阶段应急物流的时效性、经济性、风险性三个目标,将多目标优化问题转化为单目标优化,以网络总成本最小为优化目标,建立网络优化决策模型,为应急物流网络优化提供辅助决策方案.     

以商圈为中心的O2O动态外卖配送路径优化模型与算法

针对线上到线下(Online to Offline,O2O) 外卖路径优化问题,综合考虑其动态配送需求、货物区分等特点以及时间窗、载货量等约束条件,将商圈看作配送中心,将快递员数量与快递员总行驶时间作为最小化目标,提出了以商圈为中心的O2O动态外卖配送路径优化模型。采用周期性处理新订单的方法将相应的快递员路径的动态调整问题转化为一系列静态TSP子问题,设计了一种分阶段启发式实时配送路径优化算法框架,并给出了一个具体算法和一个数值计算实例。在VRP通用算例的基础上,以商圈为中心生成测试算例,对本文算法进行仿真实验,并与其他算法比较。结果表明：本文算法能充分利用新订单附近的快递员进行配送,并优化其配送路径,有效减少了快递员数量与快递员总行驶时间。     

快递企业“最后一公里”快件收派优化方案研究

本文以快递公司快件收派服务为背景,对区域收派路线规划问题进行研究,结合A快递公司实际运作情况进行案例分析,综合考虑收派混合、动态性、时间窗和容量约束四个最主要的因素,建立数学模型,设计收派流程,通过改进的禁忌搜索算法在短时间内得到优化的路径结果,并在收派活动进行中动态处理新需求及实时更新收派路径,以提高收派效率。基于该企业实际数据的计算结果表明,本文提出的相应流程和算法比实际操作获得更好的解。     

A hybrid approach integrating Affinity Diagram, AHP and fuzzy TOPSIS for sustainable city logistics planning

City logistics initiatives are steps taken by municipal administrations to ameliorate the condition of goods transport in cities and reduce their negative impacts on city residents and their environment. Examples of city logistics initiatives are urban distribution centers, congestion pricing, delivery timing and access restrictions. In this paper, we present a hybrid approach based on Affinity Diagram, AHP and fuzzy TOPSIS for evaluating city logistics initiatives. Four initiatives namely vehicle sizing restrictions, congestion charging schemes, urban distribution center and access timing restrictions are considered.The proposed approach consists of four steps. The first step involves identification of criteria for assessing performance of city logistics initiatives using Affinity Diagram. The results are four categories of criteria namely technical, social, economical and environmental. In step 2, a decision making committee comprising of representatives of city logistics stakeholders is formed. These stakeholders are shippers, receivers, transport operators, end consumers and public administrators. The committee members weight the selected criteria using AHP. In step 3, the decision makers provide linguistic ratings to the alternatives (city logistics initiatives) to assess their performance against the selected criteria. These linguistic ratings are then aggregated using fuzzy TOPSIS to generate an overall performance score for each alternative. The alternative with the highest score is finally chosen as most suitable city logistics initiative for improving city sustainability. In the fourth step, we perform sensitivity analysis to evaluate the influence of criteria weights on the selection of the best alternative.The proposed approach is novel and can be practically applied for selecting sustainable city logistics initiatives for cities. Another advantage is its ability to generate solutions under limited quantitative information. An empirical application of the proposed approach is provided.