Service load balancing,task scheduling and transportation optimisation in cloud manufacturing by applying queuing system

Recently, there is a great deal of attention in Cloud Manufacturing (CMfg) as a new service-oriented manufacturing paradigm. To integrate the activities and services through a CMfg, both Service Load balancing and Transportation Optimisation (SLTO) are two major issues to ease the success of CMfg. Based on this motivation, this study presents a new queuing network for parallel scheduling of multiple processes and orders from customers to be supplied. Another main contribution of this paper is a new heuristic algorithm based on the process time of the tasks of the orders (LBPT) to solve the proposed problem. To formulate it, a novel multi-objective mathematical model as a Mixed Integer Linear Programming (MILP) is developed. Accordingly, this study employs the multi-choice multi-objective goal programming with a utility function to model the introduced SLTO problem. To better solve the problem, a Particle Swarm Optimisation (PSO) algorithm is developed to tackle this optimisation problem. Finally, a comparative study with different analyses through four scenarios demonstrates that there are some improvements on the sum of process and transportation costs by 6.1%, the sum of process and transportation times by 10.6%, and the service load disparity by 48.6% relative to the benchmark scenario.     

Research on manufacturing grid resource service optimal-selection and composition framework

In order to address the resource service optimal-selection (RSOS) and composition problem in manufacturing grid (MGrid) system and provide high-quality service to users, an MGrid RSOS and composition framework (MGrid-RSOSCF) is investigated in this study. The process of RSOS and composition is divided into the following five steps in MGrid-RSOSCF: (1) decomposing the submitted manufacturing task into several subtasks (i.e. single resource service requested task) if the submitted task is a multiple resource service requested task; (2) searching out the qualified resource service for each decomposed subtask and generating the corresponding candidate resource service set; (3) retrieving, evaluating and comparing the quality of service (QoS) for each candidate resource service, and provide data for service optimal-selection and composition –if the submitted task is a single resource service requested task; (4) evaluating synthetically the overall quality of each candidate resource service and ranking them, and selecting the optimal one for the task – if the submitted manufacturing task is an multiple resource service requested task; (5) selecting one candidate resource service from each candidate resource service set and constructing a new composite resource service according to the submitted task requirements, and collecting all the possible resource service composite execution paths (RSCEP) and selecting the optimal paths to execute the task. The proposed MGrid-RSOSCF consists of five layers and each layer provides the corresponding necessary services and algorithms to address one problem mentioned above. The five layers are: (1) T-layer, responsible for MGrid task decomposition; (2) S-layer, responsible for resource service match and search; (3) Q-layer, responsible for QoS processing; (4) O-layer, responsible for evaluating and ranking the candidate resource service and (5) C-layer is responsible for resource service composition and optimal-selection. The case study and comparison of performances of the algorithms demonstrate that the proposed methods are sound on success rate and executing efficiency.     

混合型TOPSIS方法在多式联运服务商选择中的应用

多式联运服务商的选择是企业在国际贸易中的重要决策。针对多式联运服务的具体特点，建立了多式联运服务商选择的指标体系。考虑到信息的不确定性。以区间数形式表示定性指标值，应用混合型TOPSIS方法建立了目标优选的评价模型。最后通过一个实例对方法的有效性和实用性进行了验证。     

装备制造企业的服务模式研究:以江钻股份为例

服务作为装备制造企业提高竞争力和获得差异化竞争优势的重要来源,目前正引起越来越多国内外学者的关注。装备制造企业提供的现代服务范畴远远超过传统售后服务,还包括技术服务、渗透到顾客价值链的系统解决方案等。同时,明晰的服务愿景、技术创新能力和顾客导向是支持制造企业服务模式的关键因素。     

Reliable design of a congested disaster relief network: A two-stage stochastic-robust optimization approach

The preparedness of humanitarian relief networks can be enhanced by pre-positioning resources in strategic locations and using them when disasters strike, a strategy that gives rise to a two-stage planning problem. This paper presents a novel two-stage stochastic-robust optimization approach for integrated planning of pre- and post-disaster positioning and allocation of relief resources, while taking into consideration the uncertainty about demand for relief services and disruptions in the relief facilities and the transportation network. The proposed approach enables planners to effectively use limited historical data and imperfect experts’ opinions to obtain robust solutions while avoiding the over-conservatism of classical robust optimization methods. The objective sought is to minimize the expected total time victims need to receive assistance, including both access time to facilities and waiting/service time in them. Congestion in relief facilities is accounted for by modeling them as queuing systems and penalizing waiting time. A decomposition method based on column-and-constraint generation is implemented to solve the problem, whereas the nonlinear terms corresponding to queuing in the second-stage problem are handled using a direct search procedure. Applicability of the proposed approach is demonstrated through a real case study and the numerical results are analyzed to draw managerial insights.     

基于顾客价值的服务企业营销策略创新

随着顾客价值理论思想的建立,市场营销出现了从顾客角度看待产品和服务价值的观念。尤其对服务企业而言,顾客价值是企业竞争优势的新来源。在对顾客价值与服务企业营销创新的内在关联分析的基础上,提出了服务企业营销创新的策略,有利于提升服务企业的核心竞争力,实现企业的和谐快速发展。     

改进AHP在汽车服务备件运输方案选择中的应用

针对汽车服务备件运输方案不当所带来诸多汽车服务市场问题,在充分分析了改进AHP法的基础上,提出了基于改进AHP的汽车服务备件运输方案优化模型,并进行实例应用。结果表明：该模型提高了汽车服务备件运输方案优化的科学性、快速性及实用性,同时也为汽车制造企业制定合理的运输方案提供一定的理论依据。     

铁路公共信息服务客户满意度研究

随着运输业竞争日趋激烈,客户已成为铁路部门的重要战略资源,进行客户满意度调查与管理已成为铁路运输可持续发展的关键.本文根据专家及公众的建议,针对铁路业务类信息、延伸服务信息、常识服务信息等设计了调查问卷,运用模糊综合评价方法对调查问卷进行了评价,并对评价结果进行了分析.文章分析了造成评价结果的原因并提出了从铁路公共信息服务角度提升客户满意度的相关建议.     

A PageRank-based reputation model for personalised manufacturing service recommendation

The number of manufacturing services for cross-enterprise business collaborations is increasing rapidly because of the explosive growth of Web service technologies. This trend demands intelligent and robust models to address information overload in order to enable efficient discovery of manufacturing services. In this paper, we present a personalised manufacturing service recommendation approach, which combines a PageRank-based reputation model and a collaborative filtering technique in a unified framework for recommending the right manufacturing services to an active service user for supply chain deployment. The novel aspect of this research is adapting the PageRank algorithm to a network of service-oriented multi-echelon supply chain in order to determine both user reputation and service reputation. In addition, it explores the use of these methods in alleviating data sparsity and cold start problems that hinder traditional collaborative filtering techniques. A case study is conducted to validate the practicality and effectiveness of the proposed approach in recommending the right manufacturing services to active service users.     

Feasibility on the integration of passenger and freight transportation in rural areas: A service mode and an optimization model

Public transport operators in rural areas have been under pressure from weak profitability and emission issues. At the same time, scattered demand for transport has been preventing logistics systems from reaching the last mile in residential areas. Multimodal transport can synergistically integrate passenger and freight demand, increase transportation network coverage, and reduce the cost of transportation, while demand-driven services improve the flexibility and reliability of operational decisions. Therefore, this paper proposes a demand-driven passenger-and-freight-integration service (DDPFIS) mode. From the perspective of routing decisions, a new mixed-integer linear programming model based on the green vehicle routing problem is formulated to assist public transport operator’s complex decision-making. In the proposed model, vehicle capacity is fully utilized through a combination of passenger and freight demand so that optimal decisions are made about vehicle routing. Numerical experiments are designed and conducted based on realistic instances with the results indicating that: the DDPFIS mode enables effective integration of different demands, leading to high-level vehicle capacity utilization and cost reduction; and compared with two conventional models of vehicle routing problems, the proposed model achieves lower fuel consumption and cost for all problem sizes. In addition, some important management insights are provided, e.g., a greater proportion of integrated service nodes is not necessarily better; and it is more suitable to provide a service for rural residents who are relatively insensitive to time.     

A method towards Web service combination for cross-organisational business process using QoS and cluster

How to quickly combine various Web services to support cross-organisational business processes is the key technical problem in service computing. Because of the changeability of QoS of Web services, the traditional methods are unadaptable to the new environments. In this paper, a new service composition method, called Improved Self-organising neural network Method for Web Service Composition, is proposed to achieve QoS-aware Web service combination, according to using the clustering technology. First, fuzzy mathematics is used to express each QoS attribute and the improved self-organising neural network is used to cluster services to reduce the number of candidate services. Secondly, all the centre of each cluster is selected and formed a composite service by using an exhaustive algorithm. Thirdly, the service cluster that is represented by the concrete services. Finally, the optimal service combination can be selected using integer programming or genetic algorithm. The experimental result shows the efficiency of Web service composition and demonstrates the applicability.     

Diverse task scheduling for individualized requirements in cloud manufacturing

Cloud manufacturing (CMfg) has emerged as a new manufacturing paradigm that provides ubiquitous, on-demand manufacturing services to customers through network and CMfg platforms. In CMfg system, task scheduling as an important means of finding suitable services for specific manufacturing tasks plays a key role in enhancing the system performance. Customers’ requirements in CMfg are highly individualized, which leads to diverse manufacturing tasks in terms of execution flows and users’ preferences. We focus on diverse manufacturing tasks and aim to address their scheduling issue in CMfg. First of all, a mathematical model of task scheduling is built based on analysis of the scheduling process in CMfg. To solve this scheduling problem, we propose a scheduling method aiming for diverse tasks, which enables each service demander to obtain desired manufacturing services. The candidate service sets are generated according to subtask directed graphs. An improved genetic algorithm is applied to searching for optimal task scheduling solutions. The effectiveness of the scheduling method proposed is verified by a case study with individualized customers’ requirements. The results indicate that the proposed task scheduling method is able to achieve better performance than some usual algorithms such as simulated annealing and pattern search.     

基于服务补救的快递企业服务质量提升研究

快递服务的投诉主要集中在快件延迟、邮件丢失、邮件损坏等服务失误方面。服务失误的频繁发生会让顾客产生不满情绪,严重时会影响企业的竞争力。服务补救则为企业提供了提高顾客感知服务质量和重塑企业服务品牌和企业形象的第二次机会。对于我国快递企业而言,通过服务补救改善服务质量需要坚持责任、及时、主动、沟通等基本原则,并通过逐步建立完善的服务补救机制、给一线快递人员授权、重视一切顾客问题策略等达到提升服务质量的目标。     

Automated web service composition supporting conditional branch structures

The creation of value-added services by automatic composition of existing ones is gaining a significant momentum as the potential silver bullet in service-oriented architecture. However, service composition faces two aspects of difficulties. First, users' needs present such characteristics as diversity, uncertainty and personalisation; second, the existing services run in a real-world environment that is highly complex and dynamically changing. These difficulties may cause the emergence of nondeterministic choices in the process of service composition, which has gone beyond what the existing automated service composition techniques can handle. According to most of the existing methods, the process model of composite service includes sequence constructs only. This article presents a method to introduce conditional branch structures into the process model of composite service when needed, in order to satisfy users' diverse and personalised needs and adapt to the dynamic changes of real-world environment. UML activity diagrams are used to represent dependencies in composite service. Two types of user preferences are considered in this article, which have been ignored by the previous work and a simple programming language style expression is adopted to describe them. Two different algorithms are presented to deal with different situations. A real-life case is provided to illustrate the proposed concepts and methods.     

面向B2C及C2C业务的快递服务网点选址优化模型与算法

在分析各小区域潜在顾客群的特点及其构成的基础上,为了以最小的费用、最短的时间服务尽可能多的顾客,结合快递物流的特点,建立了混合0—1整数规划的快递服务网点的选址优化模型。该模型是一个高维、非线性、非凸性的复杂函数优化问题。为求解此模型,开发了一种改进遗传算法,实例表明,该算法能高效求得模型的最优解,是求解快递物流服务网点选址这类复杂优化问题的一个较好方法。     

Servitization: Disentangling the impact of service business model innovation on manufacturing firm performance

As manufacturing businesses operate in an ever more competitive, global economy where products are easily commoditized, innovating by adding services to the core product offering has become a popular strategy. Contrary to the economic benefits expected, recent findings pinpoint implementation hurdles that lead to a potential performance decline, the so-called ‘servitization paradox’. In this paper, we analyze this paradox by disentangling the value creation and value appropriation processes of 44 national subsidiaries of a global manufacturing firm turned product-service provider, in the 2001–2007 period. Our findings show that the firm under study is able to successfully transcend the inherent substitution of products by services and to enact complementary sales dynamics between the two activities. Moreover, labor-intensive services such as maintenance, which imply higher levels of customer proximity, further enhance product sales. Empirical results also reveal a positive yet non-linear relationship between the scale of service activities and profitability: while initial levels of servicing result in a steep increase in profitability, a period of relative decline is observed before the positive relationship between the scale of services and profitability re-emerges. These findings suggest the presence of initial short-term gains but also indicate the existence of a ‘profitability’ hurdle; profitable growth seems feasible only to the extent that investments in service capability are translated into economies of scale. In helping to clarify the performance implications of service innovation, our findings suggest pathways to sustainable growth through servitization for manufacturing firms.     

基于顾客服务水平的物流网络优化问题

文章利用优化方法讨论了供应链中由零售商向供应商订购货物,同时又要满足顾客的不确定性需求的物流网络设计问题。文中引入了顾客服务水平的概念,通过顾客的服务水平来控制库存,从而影响每次货物的订货量,并讨论了顾客需求的概率在已知和未知两种情况下,如何来确定零售商的订货量和供应商的批发价从而使得共同获利最大。此外,对顾客服务水平和零售价进行了分析,找出两者之间的关系。     

An agent-based peer-to-peer architecture for semantic discovery of manufacturing services across virtual enterprises

With the development of virtual enterprise (VE) paradigm, the usage of serviceoriented architecture (SOA) is increasingly being considered for facilitating the integration and utilisation of distributed manufacturing resources. However, due to the heterogeneous nature among VEs, the dynamic nature of a VE and the autonomous nature of each VE member, the lack of both sophisticated coordination mechanism in the popular centralised infrastructure and semantic expressivity in the existing SOA standards make the current centralised, syntactic service discovery method undesirable. This motivates the proposed agent-based peer-to-peer (P2P) architecture for semantic discovery of manufacturing services across VEs. Multi-agent technology provides autonomous and flexible problemsolving capabilities in dynamic and adaptive VE environments. Peer-to-peer overlay provides highly scalable coupling across decentralised VEs, each of which exhibiting as a peer composed of multiple agents dealing with manufacturing services. The proposed architecture utilises a novel, efficient, two-stage search strategy – semantic peer discovery and semantic service discovery – to handle the complex searches of manufacturing services across VEs through fast peer filtering. The operation and experimental evaluation of the prototype system are presented to validate the implementation of the proposed approach.     

物流企业服务创新影响因素及对策研究

物流业是生产性服务业的重要组成部分,物流服务创新不仅是物流企业增强竞争力的重要途径,对于服务经济的发展也起着至关重要的作用。文章研究的基本问题是两业联动框架中物流企业进行服务创新是否同时受到联动主体及环境因素的影响,具体有哪些因素影响物流企业的服务创新,并运用层次分析法(AHP)对这些因素进行分析。研究结果表明:影响物流企业服务创新的因素主要有物流企业因素、政府政策因素、行业环境因素、制造企业因素四个方面。     

基于产业联动的物流服务创新模式研究

物流业与其他产业的联动有助于推动物流服务模式创新和产业协同发展。文中分析了物流服务创新的影响因素,物流服务创新的理论基础,在此基础上提出了基于产业联动环境下的物流服务创新模式,包括提供全程化供应链管理创新模式、顾客化物流创新模式、物流技术创新模式和物流网络创新模式,并为其他产业的物流发展提出了参考建议。