Managing returnable transport items in a vendor managed inventory system

This paper addresses a closed-loop inventory routing problem with demand uncertainty, which manages the delivery operations to customers and pick-up operations of empty returnable transport items (RTIs) from customers. The problem involves decisions regarding forward and backward vehicle routes, the delivery and collection quantities, the amount of production in terms of the number of filled RTIs, and the number of RTIs produced/ bought by the vendor during the defined planning horizon. The problem considers the holding costs, fixed cost of operating vehicles, fuel consumption cost, producing/buying costs, cleaning costs of RTIs, and loading and unloading costs. We formulate the problem as a mixed integer linear programming model and propose a Relax and Fix based solution approach to solve large instances. We conduct extensive analyses on a case study derived from a fruit and vegetable distribution network and several hypothetical instances. Our analyses investigate the effects of several problem parameter changes (i.e., average collection rate, customer service level, cost of buying crate and handling cost) on the total logistics cost. Additional numerical analyses are performed to demonstrate the usage of the model for evaluating the cost of being more green and environmental-friendly. Moreover, experiments on relatively large-scaled problems allow us to demonstrate the potential benefits of the proposed heuristic     

Sequential clinical scheduling with patient no-show: The impact of pre-defined slot structures

This paper develops a sequential scheduling algorithm for consultation periods not divided into slots. Patients call a scheduler and request appointments with a specified provider. The scheduler provides the patient with an appointment time before the call terminates. In making the appointment, the scheduler cannot alter the appointments of previously scheduled patients. Service times are random and each scheduled patient has a probability of “no-showing” for the appointment. Each arriving patient generates a given amount of revenue, and costs are incurred from patient waiting and provider overtime. The scheduling method selects the calling patient's appointment time by minimizing the total expected cost. We prove that total expected cost is a convex function of appointment times and that the expected profit of the schedule is unimodal, which provides a unique stopping criterion for the scheduling algorithm. Computational studies compare this approach with no-show based sequential scheduling methods for out-patient clinics where a predefined slot structure is assumed. The new method yields higher expected profit and less overtime than when service periods are pre-divided into slots. Because slot scheduling is ingrained in healthcare, we use the model to design slot structures that account for no-show and service time variation.     

Internet of things (IoT) platform competition: Consumer switching versus provider multihoming

Internet of things (IoT) brings new opportunities and represents a new source of welfare and efficiency. However, the emerging consumer IoT platform competition creates the risk of monopoly power due to network effects. Overall, it is likely that both competition (incentivized through lowering consumer switching costs) and cooperation (achieved through interoperability, which enables data portability and service provider multihoming) are needed to maximize social welfare. This article aims to address how consumer switching costs and provider multihoming affect competition of emerging consumer IoT data platforms under different market conditions and regulatory schemes. It utilizes agent-based modelling that is especially suitable when decision making is distributed at a micro level while some rules are applied in a centralized fashion. The obtained findings emphasize the role of the regulator in guiding the market. It seems that when switching costs diminish at all sides of the platforms, consumers and service providers will favour the platform with a higher number of users. Further, service provider multihoming mitigates market concentration on both sides of a platform when switching costs are low. Thus, there seems to be a minimum level of interoperability needed to promote market competition. Further, although data portability gives more freedom to consumers in choosing a platform provider, it may result in a winner-takes-all situation due to strong indirect network effects.     

云端数据管理系统的设计

互联网的快速发展使每日产生的庞大数据的存储和冗余备份,成为技术领域亟待解决的问题,低成本高效运行的数据存储管理系统成为研究的主流,本文的研究目标是基于云计算技术的云端数据管理系统,实现从普通用户到企业用户的云端数据存储、数据检索和相应的管理服务,同时支持系统的快速可扩展以及数据备份和安全恢复。     

Interaction of maritime shipping and hinterland traffic using a two-level hierarchical transport network

A transport scenario based on a two-level network is developed in order to model operations in maritime transport. To enhance competitiveness and sustainability of shipping companies, the interaction between maritime shipping and hinterland traffic is considered in the novel two-level hierarchical transport network. Demand occurs on the second level, the hinterland, whereas the first level, the sea transport, acts as a pure distribution network. The two-level hierarchical transport model allows regulating the degree of interaction a liner operator has regarding the hinterland traffic. Moreover, access of vehicles to nodes or edges is given subject to feasibility constraints, relating to the size of a vehicle. In this work, the relation to existing routing models, such as the travelling salesman problem, the vehicle routing problem, or the travelling purchaser problem, is illustrated. Moreover, through the definition of a proper set of assumptions, it is possible to reduce the considered two-level hierarchical transport network to different standard routing models. These new insights allow the application of existing solution methods. Numerical experiments are conducted for a particular case and illustrate the influence of node costs on the distribution of workload to the vehicles.     

Analysing the impact of restructuring transportation,production and distribution on costs and environment – a case from the Thai Rubber industry

Transportation and distribution are key elements to successful supply chains, however there is some disagreement regarding the impact of distribution and transportation restructuring on costs and the environment. This paper explores the use of an optimisation model of Thailand’s rubber industry supply chain, to assess the impact of distribution and transportation on costs and greenhouse gas emissions. It has previously been observed that there is a positive correlation between transportation cost reduction and environmental impact, nevertheless the correlation is not clearly established when the distribution system is restructured. This paper is divided into two parts: the first part examines the impact of transportation service capacity on distribution decisions; the second part of the paper aims to examine the impact of restructuring the distribution network considering multi-modal options on cost and greenhouse gas emissions. For both parts a scenario analysis is utilised in conjunction with an optimisation model to derive the best possible answer in terms of costs and GHG emissions. In this paper, the results obtained indicate that the impact on cost minimisation from the increase in rail freight service capacity is marginal, while the impact on GHG emission minimisation is more significant. In terms of short-sea shipping prices and service capacity, the scenario analysis shows a slight positive impact on cost minimisation but no positive or negative impact on GHG emission minimisation. Results also confirm that in terms of economic advantages, distribution network restructuring provides greater benefit to the industry than does capacity development for the transportation service.     

What is a strategic acquisition? Decision modeling in support of foreclosed housing redevelopment

This paper describes and develops a model for calculating location-based strategic values of foreclosed properties considered for acquisition and redevelopment by community development corporations (CDCs). A property’s strategic value refers to its proximity to site-specific neighborhood amenities and disamenities (e.g. schools, public transit, distressed properties), given the relative importance of that proximity to CDC organizational and community objectives. We operationalize the concept of strategic value, and apply this concept to a salient public sector decision problem. Using data and value assessments from a CDC engaged in foreclosed housing redevelopment, we compute measures of strategic value for a set of acquisition candidates. We show that strategic values can differ in systematic ways depending on the types of amenities and disamenities identified as relevant for CDC acquisition decisions, the relative importance assigned to those amenities and disamenities, and the utility maximization objectives of the CDC. We conclude by proposing a multi-criteria decision model for foreclosed housing acquisition and redevelopment which incorporates a theory of residential housing impacts for which strategic value measures are a special case.     

云计算与信息安全

信息安全是当前计算机科学的一个研究热点;云计算是一个新的技术,给信息安全提供了挑战和机遇。介绍了云计算的基本概念、云计算的安全问题,通过云计算用户以及云计算服务提供商两方面分析了云计算中确保信息安全的方法。     

分布式存储系统调查

随着现代IT系统的发展,数据的规模越来越庞大,并且增速也越来越快,因此传统的存储系统遇到了前所未有的挑战。目前,已经有很多公司和组织使用分布式存储系统对其海量数据进行存储和管理,并且越来越多的其他用户也希望能够将其应用于云存储系统中,从而获得更好的性能和更低廉的价格。分布式存储系统作为云存储技术的基础得到了越来越广泛的应用,其中存储虚拟化常常被用于私有云存储的方案中,而面向对象的存储和分布式文件系统被更多地应用于公有云的系统中。文章介绍了目前流行的分布式存储系统,并为用户选择分布式存储系统提供参考。     

鲜活农产品冷链物流配送路径优化研究

本文以传统的配送路径优化问题为基础,针对鲜活农产品易变质、易腐蚀的特性,指出了冷链物流的概念和重要意义。通过对冷链配送过程中产生的固定成本、运输成本、货损成本、惩罚成本的研究,构建了带时间窗的鲜活农产品冷链物流配送的成本模型,并对路径优化算法进行了简化,最后通过算例验证了模型和算法的准确性、合理性和可行性。     

Health Care Payment Systems: Cost and Quality Incentives

This paper compares the cost and quality incentive effects of cost reimbursement and prospective payment systems in the health industry. When a provider cannot refuse patients who require high treatment costs or discriminate patients by qualities, optimally designed prospective payments can implement the efficient quality and cost reduction efforts, but cost reimbursement cannot induce any cost incentive. When the provider can refuse expensive patients, implementation of the first best requires a piecewise linear reimbursement rule that can be interpreted as a mixture of pure prospective payment and pure cost reimbursement, Under appropriate conditions, prospective payment can implement the first best even when the provider can use qualities to discriminate patients.     

基于时间约束的物流运输路线优化

在分析车辆运输费用和运输时间的基础之上,建立一个以规定时间内最小费用为目标的物流调度路线优化数学模型。同时给出车辆路线问题的求解算法思路和计算流程,并结合实例,采用Dijkstra迭代方法,讨论该算法的应用。从而为在物流调度的车辆运输路线优化中实现在满足时间约束条件下达到运输费用最低提供依据和方法。     

基于蚁群算法考虑路线安排的单配送中心选址

对一类要求考虑路线安排的单配送中心选址问题建立基于蚁群算法的选址模型,模型目标以配送中心建设费用与运输费用之和最小;同时构造模型的蚁群算法求解结构;最后初步应用证明了该模型解决此类问题的有效性,为单配送选址提供又一种方法。     

产品生命周期成本及其成本结构权衡理论研究——一种增量成本优化的研究方法

随着市场竞争程度的加强和产品寿命周期的缩短,对产品全寿命周期成本分析就显得非常重要。本文从企业的角度(生产者视角的产品寿命周期成本)采用价值链分析方法和增量成本分析方法讨论产品寿命周期成本与产品价值,以及产品寿命周期内各阶段成本结构的优化问题。将产品价值与产品寿命周期成本进行对比和优化从而为企业价值最大化和满足顾客需求提供判断依据。     

Why internet service provider and content provider do not collaborate via monitoring of digital piracy

Internet service providers (ISPs) and content providers (CPs) have a symbiosis relationship in the Internet business ecosystem. In this paper, we investigate the possibility of and the conditions for their revenue sharing by means of on-line content piracy monitoring. CPs can benefit from the efforts of ISPs to monitor illegal content consumers, and can have the incentives to collaborate with ISPs. We suggest that if the quality degradation of a pirated content is low as in real world, there may not be a successful collaboration because CPs have little incentives to share their revenues with ISPs. We also investigated the impacts of ISP's piracy monitoring cost level, the value of contents, and CP's access fee per traffic on the possibility of their collaboration.     

基于云计算的B2C电子商务企业价值链优化

云计算通过互联网为用户提供动态可扩展的、虚拟的、按需付费的计算资源。云计算的应用能够降低数据计算、数据处理服务的使用成本,计算资源的使用方式更加灵活和便捷。这将促使更多的企业进入电子商务领域、更多的用户进行网上交易,进而推动企业和消费者间即B2C电子商务的大规模发展。本文研究云计算对电子商务发展环境的影响,基于价值链理论探讨B2C电子商务企业如何在云计算环境下获得持续发展和提高竞争力。     

以均衡为目标的车辆调度问题研究

针对物流配送企业私人承包车辆以及均衡配送线路工作量等新的物流管理理念,提出新的车辆调度模型,将车辆调度问题（VRP）转换为车辆选型和车辆路径优化两个子问题,设计Ak-FirstFit混合算法解决车辆选型问题,运用遗传算法解决车辆路径问题。基于JAVA编写计算机程序,运行结果表明该两阶段算法能够在有效时间内得到满意解。与基于传统物流管理理念的模型进行比较,得出新的两阶段模型能充分体现兼顾效率与公平思想的结论,其理念在物流配送企业中具有相当的借鉴性和推广前景。     

浅析物流门的设置对工厂物流的影响

减少物料搬运工作量是减少物汉成本的一个重要方面。通过利用系统平面布置法（简称ＳＬＰ）对某摩托车厂的平面布置进行分析,得出物流流门的设置可以大大减少物料搬运工作量,达到降低成本的目的。     

对项目采购成本控制的几点思考

采购成本在项目总成本中占据重要地位,项目采购成本控制对企业最终利润形成具有"杠杆效应"。在采购理念日新月异的新形势下,如何正确认识项目采购成本问题并对不同性质的采购产品选择合适的采购方法,是当前项目采购管理急需面对的问题。基于近年来国际上出现的采购新理念,本文对影响项目采购成本的主要因素以及传统采购成本管理的主要弊端进行了分析,并提出了降低采购成本的解决思路。     

The effect of lot-sizing on workload variability

Lot-sizing models which group demand requirements for one or more consecutive time periods into a single production run have received considerable attention in recent years. Material Requirements Planning (MRP) systems must, for instance, make a lot-size decision for each planned order release. Existing decision models attempt to minimize the sum of setup plus inventory holding costs. However, lot-sizing tends to increase the work center load variability, and, consequently, the costs associated with changing production levels from period to period should be incorporated into the economic analysis. This study is concerned, first of all, with analytically describing the relationship between dynamic lot-sizing models and workload variability. Secondly, in order to account for production level change costs we propose a simple modification to existing heuristic models. Lastly, we employ a simulation model to empirically extend these results to a typical MRP multiechelon production environment. An example is included to show clearly that with cost premiums for overtime and severance or guaranteed minimum costs for undertime the traditional lot-sizing techniques significantly underestimate actual costs and can lead to very costly policies.Mean, variance and coefficient of variation of period work time requirements are derived as a function of several algorithm characteristics. Average cycle time (number of periods covered by a single batch) is found to be the most influential factor in determining workload variability. Variance grows approximately in proportion to this cycle time with the proportionality constant being the square of average period workload. Cycle time and demand variability also contribute to workload variability. Results indicate that for a given average cycle time, the EOQ method will minimize workload variability. When N products utilize the same work center, the coefficient of load variation will be reduced by a factor of N^{?$\text{1}\text{2}$} unless requirements are positively correlated. Positive correlation would result when products have similar seasons or parent items. In this case grouping such products cannot help reduce variability.In order to incorporate production level change costs into existing heuristics we may simply introduce a term consisting of a penalty factor times average cycle time. The penalty factor represents the costs of period by period production level changes. Several popular heuristics are extended in this fashion, and it is found that solutions are still readily obtainable, requiring only modifications to setup or holding cost parameters.The effects of level change costs are examined via simulation for a specific yet typical environment. It is found that when setup costs are significant, traditional lot-sizing heuristics can provide cost savings and service level improvements as compared to lot-for-lot production. However, whereas for our model the obtainable profit improvement from lot-sizing was 25% in the case of freely variable capacity, actual improvements were only one half as large when reasonable hiring and firing practices and overtime and undertime costs were considered. Consequently, management needs to consider carefully labor costs and work center product relationships when determining a production scheduling method.