Assessing a cross-border logistics policy using a performance measurement system framework: the case of Hong Kong and the Pearl River Delta region

For the most rapidly growing economic entity in the world, China, a new logistics operation called the indirect cross-border supply chain model has recently emerged. The primary idea of this model is to reduce logistics costs by storing goods at a bonded warehouse with low storage cost in certain Chinese regions, such as the Pearl River Delta (PRD). This research proposes a performance measurement system (PMS) framework to assess the direct and indirect cross-border supply chain models. The PMS covers four categories including cost, time, quality and flexibility in the assessment of the performance of direct and indirect models. Furthermore, a survey was conducted to investigate the logistics performance of third party logistics (3PLs) at the PRD regions, including Guangzhou, Shenzhen and Hong Kong. The significance of the proposed PMS framework allows 3PLs accurately pinpoint the weakness and strengths of it current operations policy at four major performance measurement categories. Hence, this helps 3PLs further enhance the competitiveness and operations efficiency through better resources allocation at the area of warehousing and transportation.     

A bi-level programming for logistics network design with system-optimized flows

This paper proposes a bi-level programming for a logistics network design problem with system-optimized flows. We applied the Wardrop’s second principle to the logistics network design problem. A system-optimized logistics network design problem can be formulated as a bi-level program. For the system-optimized flows, a user equilibrium traffic assignment problem with marginal costs can be solved at the lower level problem. Due to the non-differentiability of the perturbed solutions in system-optimized flows, we present a novel solution algorithm to efficiently solve the logistics network design problem. By using the subgradients of the objective function, a new projection method is proposed with global convergence. Numerical calculations are implemented using a grid-size hypothetical network and comparisons are made with other alternatives in solving the logistics network design problem. Numerical results disclose that the proposed method has successful solved the logistics network design problem and achieved significant performance both in computational efficacy and cost reduction when compared to other alternatives.     

A hybrid fuzzy goal programming approach with different goal priorities to aggregate production planning

In this study a hybrid (including qualitative and quantitative objectives) fuzzy multi objective nonlinear programming (H-FMONLP) model with different goal priorities will be developed for aggregate production planning (APP) problem in a fuzzy environment. Using an interactive decision making process the proposed model tries to minimize total production costs, carrying and back ordering costs and costs of changes in workforce level (quantitative objectives) and maximize total customer satisfaction (qualitative objective) with regarding the inventory level, demand, labor level, machines capacity and warehouse space. A real-world industrial case study demonstrates applicability of proposed model to practical APP decision problems. GENOCOP III (Genetic Algorithm for Numerical Optimization of Constrained Problems) has been used to solve final crisp nonlinear programming problem.     

A goal programming model for aggregate production planning with resource utilization constraint

This paper addresses the aggregate production planning problem with different operational constraints, including production capacity, workforce level, factory locations, machine utilization, storage space and other resource limitations. Three production plants in North America and one in China are considered simultaneously. A pre-emptive goal programming model is developed to maximize profit, minimize repairing cost and maximize machine utilization of the Chinese production plant hierarchically. A set of data from a surface and materials science company is used to test the effectiveness and the efficiency of the proposed model. Results illustrate the flexibility and the robustness of the proposed model by adjusting goal priorities with respect to importance of each objective and the aspiration level with respect to desired target values.     

Credibility-based fuzzy mathematical programming model for green logistics design under uncertainty

Measuring and controlling emissions across the logistics network is an important challenge for today’s firms according to increasing concern about the environmental impact of business activities. This paper proposes a bi-objective credibility-based fuzzy mathematical programming model for designing the strategic configuration of a green logistics network under uncertain conditions. The model aims to minimize the environmental impacts and the total costs of network establishment simultaneously for the sake of providing a sensible balance between them. A popular but credible environmental impact assessment index, i.e., CO₂ equivalent index is used to model the environmental impact across the concerned logistics network. Since transportation mode and production technology play important roles on the concerned objectives, the proposed model integrates their respective decisions with those of strategic network design ones. In addition, to solve the proposed bi-objective fuzzy optimization model, an interactive fuzzy solution approach based upon credibility measure is developed. An industrial case study is also provided to show the applicability of the proposed model as well as the usefulness of its solution method.     

A sparse Gaussian process regression model for tourism demand forecasting in Hong Kong

In recent years, Gaussian process (GP) models have been popularly studied to solve hard machine learning problems. The models are important due to their flexible non-parametric modeling abilities using Mercer kernels and the Bayesian framework for probabilistic inference. In this paper, we propose a sparse GP regression (GPR) model for tourism demand forecasting in Hong Kong. The sparsification procedure of the GPR model not only decreases the computational complexity but also improves the generalization ability. We experiment the proposed model with monthly demand data that are relevant to Hong Kong’s tourism industry, and compare the performance of the sparse GPR model with those of various kernel-based models to show its effectiveness. The proposed sparse GPR model shows that its forecasting capability outperforms those of the ARMA model and the two state-of-the-art SVM models.     

A strategic knowledge-based planning system for freight forwarding industry

In recent years, over half of the Hong Kong freight forwarding firms experienced a decline in business volume due to the growing challenge from the neighbour ports of Yantian and Shekou in Shenzhen, China, which operated in a much cheaper mode. In order to remain competitive, local freight forwarders in Hong Kong must establish a long-term union relationship with their customers such as the provision of customized logistics services. One of the ways is through the use of a co-loading shipment plan, which is a knowledge intensive and complex process involving multiple knowledge source and decision rules. This paper presents hybrid knowledge and model system, which integrates mathematical models with knowledge rules, in the formulation of such co-loading shipment plans. A strategic knowledge-based planning system, (SKPS) integrates knowledge rules with mathematical model for solving problems of co-loading shipment plans formulation and market constriction prevention, is proposed. The system was implemented in Elite World Logistics Service Limited (EW), a local freight forwarding company, for supporting the planning process of a co-loading shipping plan. The result reveals that both customer retention rate and resource utilization has increased significantly.     

跨境金融物流服务创新及保税物流园区个案分析

In the middle of current finance tsunami, there demand measures from the governments across the border between Hong Kong and Mainland to alleviate the financing difficulties faced by the Hong Kong invested enterprises in Pearl River Delta (PRD). The paper describes the issues surrounding how innovative logistics techniques can be used to overcome border barriers to provide financing services to Hong Kong invested Processing Trade Enterprises (PTE) in PRD. The problems are identified for cross board financing. An analysis tool through risk transfer diagram is developed for service identification. Different financing instruments are reviewed using the tool developed in which the necessary financing logistics functions are identified. Service architecture is given for these financing logistics functions. A case study for cross border financing development in the context of bonded logistics parks shows that a cross border financing logistics park could be a viable approach to facilitating cross border financing development.     

Historical Trajectories of Innovation and Competitiveness: Hong Kong Firms and their China Linkages

Hong Kong manufacturing firms have been competing in world markets since the 1950’s. Their success has been based on low cost and flexible production and an ability to meet very tight delivery schedules as many of their products are short run fashion items for which consumer demand can be fickle. The opening of China in 1978 has enabled Hong Kong firms to sustain their cost advantages in world markets for a further twenty years. However, the rapid economic development of South China in particular, to which Hong Kong is adjacent, and the competition from lower cost economies in Southeast Asia is leading to pressures on Hong Kong manufacturers to rethink their strategies. Ambitions to continue to compete among world class manufacturers has become a survival strategy. The focus of this paper is to identify and explain the historical development of innovation in the strategies of Hong Kong firms to enable them to continue to dominate niche markets in Europe and the USA and develop a presence in the China market.     

A framework for a logistics e-commerce community network: the HongKong air cargo industry

E-commerce has brought new challenges as well as opportunities to the air cargo industry. With careful planning and cooperation among industry agents and with e-commerce as an enabler the air cargo industry can be transformed into one that can provide customized services to individual shippers at the cost level of mass production. The key component is in the setting up of a third-party e-commerce community network. In this paper, we present a frame work for such a network, which extends the traditional business-to-business e-commerce to e-commerce at the industry level. The proposed infrastructure differs from traditional portals in that it features the online integration of business transactions. It provides a virtual market for agents of the air cargo industry, enabling them to develop and engage in logistics integration. It also facilitates tracking and tracing, and minimizes unnecessary travel and inventory costs, thus achieving supply chain management at the industry level. We provide an implementation scenario for the air cargo industry in Hong Kong     

Two Machine Scheduling under Disruptions with Transportation Considerations

Effective logistics scheduling requires synchronization of manufacturing and delivery to optimize customer service at minimum total cost. In this paper, we study a new scheduling problem that arises in a disruption environment. Such a problem occurs when a disruption unexpectedly happens, and consequently, some machines become unavailable for certain periods. Jobs that are assigned to the disrupted machines and have not yet been processed can either be moved to other available machines for processing, which may involve additional transportation time and cost, or can be processed by the same machine after the disruption. Our goal is to reschedule jobs so that an objective function, including the original cost function, and possibly transportation costs and disruption cost caused by deviating from the originally planned completion times, is minimized. In this paper, we focus on the two-machine case to demonstrate some major properties, and hope that these properties can provide insights for solving other general problems, such as multiple (more than two) machine scheduling and machine scheduling in other configurations (job shop or flow shop) under disruption. We study problems with different related costs. In each problem, we either provide a polynomial algorithm to solve the problem optimally, or show its NP-hardness. If the problem is NP-hard in the ordinary sense, we also present a pseudo-polynomial algorithm to solve the problem optimally. This research is supported in part by Hong Kong RGC grant HKUST 6145/03E and in part by NSF Grant DMI-0300156.     

A geometrical solution to time series searching invariant to shifting and scaling

The technique of searching for similar patterns among time series data is very useful in many applications. The problem becomes difficult when shifting and scaling are considered. We find that we can treat the problem geometrically and the major contribution of this paper is that a uniform geometrical model that can analyze the existing related methods is proposed. Based on the analysis, we conclude that the angle between two vectors after the Shift-Eliminated Transformation is a more intrinsical similarity measure invariant to shifting and scaling. We then enhance the original conical index to adapt to the geometrical properties of the problem and compare its performance with that of sequential search and R^*-tree. Experimental results show that the enhanced conical index achieves larger improvement on R^*-tree and sequential search in high dimension. It can also keep a steady performance as the selectivity increases. Part of the result related to the geometrical model has been published in the Proceedings of the 18th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, pp 237–248. Mi Zhou was born in China. He received his BS and MS degrees in computer science from the Northeastern University, China, in 1999 and 2002, respectively. He is currently pursuing the Ph D degree in the Computer Science and Engineering Department, The Chinese University of Hong Kong. His research interests include indexing of time series data, high-dimensional index, and sensor network. Man-Hon Wong received his BSc and MPhil degrees from The Chinese University of Hong Kong in 1987 and 1989 respectively. He then went to University of California at Santa Barbara where he got the PhD degree in 1993. Dr. Wong joined The Chinese University of Hong Kong in August 1993 as an assistant professor. He was promoted to associate professor in 1998. His research interests include transaction management, mobile databases, data replication, distributed systems, and computer and network security. Kam-Wing Chu was born in Hong Kong. He received his BS and MPhil degrees in computer science and engineering from The Chinese University of Hong Kong. When he was in Hong Kong, his research interests included database indexing of high dimensional data, and data mining. He later went to United States and received his MS degree in computer science from University of Maryland at College Park. While he was in Maryland, he focused on high performance implementation and algorithm design of advanced database systems. He is currently a senior software engineer in Server Performance group at Actuate Corporation. His expertise is in enterprise software development and software performance optimization.     

An iterated construction approach with dynamic prioritization for solving the container loading problems

This paper addresses the single and multiple container loading problems, which forms the core engine of a warehouse management system we are contracted to implement for a Hong Kong logistics company. We propose to use dynamic prioritization to handle the awkward box types, whereas the box type with a higher priority is packed onto lower surfaces of the container for the single container case, or packed in earlier containers for the multiple container case. The solution found in one iteration of the algorithm is analyzed, and the priorities are updated and used in the next iteration. This approach provides very competitive results using standard benchmark data sets as compared with other methods. It helps to reduce the difficulty in system implementation and maintenance, because the algorithm is easy to understand for practitioners in the local industry, and it is applicable for both the single and multiple container loading problems at the same time. In addition, we find the existing test data for the multiple container loading problem to be deficient and supplement them by generating new test data consisting of 2800 test cases. Last but not least, our algorithm has been packaged into a software component with full graphical user interface and integrated into a warehouse management system for daily operations.     

粤港跨境数字证书认证技术研究

针对粤港两地政策法规未完全规范,以及两地数字证书认证机构(CA)在认证业务声明和证书策略两方面存在差异的问题,分析目前跨域公钥基础设施信任架构,提出一种针对当前两地政策法规未完全规范情况下的跨境认证解决方案。采用签名中转以及证书信任列表技术,构建两地 CA互认支撑平台。实践结果证明,该方案适合于点对点的 CA互认,为建设中国与上合组织、东盟、澳大利亚等国家和区域的跨境认证奠定了基础。     

Students' views of collaboration and online participation in Knowledge Forum

This study examined students’ views of collaboration and learning, and investigated how these predict students’ online participation in a computer-supported learning environment. The participants were 521 secondary school students in Hong Kong, who took part in online collaborative inquiry conducted using Knowledge Forum™. We developed a questionnaire to assess the students’ views of their collaboration aligned with the knowledge-building perspective. We also administered the Learning Process Questionnaire to examine their preferred approaches to learning. The students’ online participation in Knowledge Forum was examined using the Analytic Toolkit software. Analyses indicated that students who viewed their collaboration as more aligned with collaborative knowledge building were more likely to employ a deep approach to learning. A structural equation model indicated that the students’ views of collaboration exerted a direct effect on online participation in Knowledge Forum and mediated the effects of deep approaches on forum participation. Implications of examining students’ views of collaboration for productive online participation are discussed.     

Reentry Trajectory Optimization for Hypersonic Vehicles Using Fuzzy Satisfactory Goal Programming Method

Constrained reentry trajectory optimization for hypersonic vehicles is a challenging job. In particular, this problem becomes more difficult when several objectives with preemptive priorities are expected for different purposes. In this paper, a fuzzy satisfactory goal programming method is proposed to solve the multi-objective reentry trajectory optimization problem. Firstly, direct collocation approach is used to discretize the reentry trajectory optimal-control problem with nonlinear constraints into nonlinear multiobjective programming problem with preemptive priorities, where attack angles and bank angles at nodes and collocation nodes are selected as control variables. Secondly, the preemptive priorities are transformed into the relaxed order of satisfactory degrees according to the principle that the objective with higher priority has higher satisfactory degree. Then the fuzzy satisfactory goal programming model is proposed. The balance between optimization and priorities is realized by regulating parameter λ, such that the satisfactory reentry trajectory can be acquired. The simulation demonstrates that the proposed method is effective for the multi-objective reentry trajectory optimization of hypersonic vehicles.     

Available-to-promise based bidding decision by fuzzy mathematical programming and genetic algorithm

The present study attempts to integrate bidding decisions with order promising and production planning to enhance supplier profitability and service level. This study formulates the bid price and production plan as a mixed integer programming model with fuzzy constraints. The fuzzy constraints represent the decision-maker’s subjective judgment regarding the customer’s price tolerance. The proposed model combines the advanced available-to-promise (AATP) concept to find optimum resource allocation and enable accurate estimations of production costs and delivery dates. The proposed solution procedure determines the optimum bid price by striking a compromise between profitability and the possibility to win the contract. This study develops a genetic algorithm to solve this problem, and provides computer simulated experiments to evaluate the performance of the proposed approach.     

Value engineering in Hong Kong — a powerful tool for a changing society

Hong Kong, one of the most dynamic cities in Asia if not the world, has been changing rapidly in recent years as a result of technological advancement, fierce local and international competition, and ever-increasing customer requirements. In addition, as design and production costs become more significant, different cost control techniques and the means of achieving better value for money are becoming increasingly important. Value engineering (VE) is one way to improve efficiency and seek the best balance between the cost, reliability and performance of a product or service. Though value engineering is still in its infancy in Hong Kong, there are already signs that value engineering is being used in the private and public sectors. This paper highlights the current development of value engineering in Hong Kong in terms of owners' acceptance of it. Details of VE education, research and professional institution in Hong Kong are also given.     

基于节点流的流程工业生产物流调度方法及应用

流程工业生产物流动态平衡调度是典型的多工序、多目标、多约束的多机并行调度问题,难以解析建模.为此,提出了节点流控制及切换的概念,建立了生产调度模型,并采用多目标分层求解调度模型.在此基础上,提出了流程工业生产的物流平衡调度方法.实际应用表明,所提出方法提高了物流动态调度的准确性和生产效率.