Henry C. W. Lau

Global supplier selection: a fuzzy-AHP approach

Global supplier selection has a critical effect on the competitiveness of the entire supply chain network. Research results indicate that the supplier selection process appears to be the most significant variable in deciding the success of the supply chain. It helps in achieving high quality products at lower cost with higher customer satisfaction. Apart from the common criteria such as cost and quality, this paper also discusses some of the important decision variables which can play a critical role in case of the international sourcing. The importance of the political-economic situation, geographical location, infrastructure, financial background, performance history, risk factors, etc., have also been pointed out in particularly in the case of global supplier selection. Supplier selection problem related to the global sourcing is more complex than the general domestic sourcing and as a result it needs more critical analysis, which could not be found properly in past available literatures. This paper discusses the fuzzy based Analytic Hierarchy Process (fuzzy-AHP) to efficiently tackle both quantitative and qualitative decision factors involved in selection of global supplier in current business scenario. The fuzzy-AHP is an efficient tool to tackle the fuzziness of the data involved in deciding the preferences of the different decision variables involved in the process of global supplier selection. The triangular fuzzy numbers are used to transform the linguistic comparison of the different decision criteria, sub-criteria and performance of the alternative suppliers. The pairwise comparison matrices help in deciding the synthetic extent value of each comparison and finally, the priority weights of one alternative over another are decided in this paper. An example from a manufacturing industry searching for the global supplier for a critical component is used to demonstrate the effective implementation procedure of proposed fuzzy-AHP technique. The proposed model can provide the guidelines and directions for the decision makers to effectively select their global suppliers in the current competitive business scenario.

A hybrid genetic algorithm for the multi-depot vehicle routing problem

The distribution of finished products from depots to customers is a practical and challenging problem in logistics management. Better routing and scheduling decisions can result in higher level of customer satisfaction because more customers can be served in a shorter time. The distribution problem is generally formulated as the vehicle routing problem (VRP). Nevertheless, there is a rigid assumption that there is only one depot. In cases, for instance, where a logistics company has more than one depot, the VRP is not suitable. To resolve this limitation, this paper focuses on the VRP with multiple depots, or multi-depot VRP (MDVRP). The MDVRP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To deal with the problem efficiently, two hybrid genetic algorithms (HGAs) are developed in this paper. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method and the nearest neighbor heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different problem sizes. It is proved that the performance of HGA2 is superior to that of HGA1 in terms of the total delivery time.

A RFID case-based logistics resource management system for managing order-picking operations in warehouses

In the supply chain, a warehouse is an essential component for linking the chain partners. It is necessary to allocate warehouse resources efficiently and effectively to enhance the productivity and reduce the operation costs of the warehouse. Therefore, warehouse management systems (WMSs) have been developed for handling warehouse resources and monitoring warehouse operations. However, it is difficult to update daily operations of inventory level, locations of forklifts and stock keeping units (SKUs) in real-time by using the bar-code-based or manual-based warehouse management systems. In this paper, RFID technology is adopted to facilitate the collection and sharing of data in a warehouse. Tests are performed for evaluating the reading performance of both the active and passive RFID apparatus. With the help of the testing results, the efficient radio frequency cover ranges of the readers are examined for formulating a radio frequency identification case-based logistics resource management system (R-LRMS). The capabilities of R-LRMS are demonstrated in GSL Limited. Three objectives are achieved: (i) a simplification of RFID adoption procedure, (ii) an improvement in the visibility of warehouse operations and (iii) an enhancement of the productivity of the warehouse. The successful case example proved the feasibility of R-LRMS in real working practice.

A conceptual model of performance measurement for supply chains

Supply chain management (SCM) has gained a tremendous amount of attention from both industries and researchers since the last decade. Until now, there are numerous papers, articles, and reports that address SCM, but there is still a lack of integration between the existing performance measurement methods and practical requirements for the SCM. An innovative performance measurement method is proposed to provide necessary assistance for performance improvement in SCM. The proposed method will address this purpose in these four aspects: a simplified supply chain model; tangible and intangible performance measures in multiple dimensions; a cross‐organizational performance measurement; and fuzzy set theory and weighted average method.

A knowledge-based supplier intelligence retrieval system for outsource manufacturing

Knowledge management is to promote business success through a formal, structured initiative to improve the use of knowledge in an organization, in which an effective organizational memory information system plays an increasingly important role. Unlike the past, the performance of an enterprise now depends much on the performance and relationship of its customer–suppliers in the value chain. Good customer–supplier relationships are important for an organization to respond to dynamic and unpredictable changes. This paper describes a knowledge-based supplier selection and evaluation system, which is a case-based reasoning decision support system for outsourcing operations at Honeywell Consumer Products (Hong Kong) Limited in China. As a result, collaborative suppliers are identified quickly during the new product development process. By using the system, the cumulative performance of suppliers is constantly updated automatically according to past practice. This means that the knowledge of suppliers can be retained, categorized, retrieved and managed effectively.

Integration of expert system with analytic hierarchy process for the design of material handling equipment selection system

Abstract A key task in the material handling system design process is the selection and configuration of equipment for material transport and storage in a facility. Material handling equipment selection is a complex, tedious task, and there are few tools other than checklists to assist engineers in the selection of appropriate, cost-effective material handling equipment. This paper describes the development of an intelligent material handling equipment selection system called material handling equipment selection advisor (MHESA). The MHESA is composed of three modules: (1) a database to store equipment types with their specifications; (2) a knowledge-based expert system for assisting material handling equipment selection; and (3) an analytic hierarchy process (AHP) model to choose the most favorable equipment type. The concept proposed in this paper can automate the design of a material handling equipment selection system, and provides artificial intelligence in the decision-making process.

A review of the Chinese cultural influences on Chinese enterprise management

In order to create and sustain competitive advantage, a company should not only develop technologies to create products and processes that meet customer needs, but also stimulate a corporate culture that commits to continuous performance improvement. Managing corporate culture is one of a number of important factors that make for organizational change and business success. This paper reviews the cultural roots and identifies the characteristics of Chinese cultural values and management. A comparative analysis of the differences between Anglo-American and Chinese cultures is made. The cultural influences on Chinese management systems are then elaborated with reference to enterprise management in Mainland China and Hong Kong. With unique cultural heritage, collective orientation has a pervasive influence on the mode of Chinese management and organization. The prevailing Chinese culture values stress largely the paternalistic approach to management, acceptance of hierarchy and the importance of relationships. Todays Chinese enterprises need to determine changes in practice or value or both aspects of corporate culture in order to facilitate organizational change and maintain a competitive edge over their rivals. The paper also discusses the links of cultural values to employee involvement (EI) and total quality management (TQM), and initiates a need to manage cultural influences on EI/TQM practices to improve organizational performance in Chinese enterprises.

A decision support system for supplier selection in the airline industry

Abstract Supplier selection has increasingly been regarded as one of the most important strategies in the globalization era. While many companies require different resources from the supply market, airline companies require supplies of parts and repair and maintenance services. The suppliers of these products and services are regarded as critical for the industry. With the multidimensional nature of the problem, supplier selection involves both tangible and intangible selection criteria. This paper presents a case study on solving the supplier selection problem in the airline industry through a decision support system that employs the analytical hierarchy process (AHP). The system was implemented with the aid of the commercial software package Expert Choice. The significance of the study is to provide a new platform for airline companies in selecting suppliers on the basis of the proposed decision support system, which was tested with a Hong Kong-based airline company during the course of development. In addition, the model highlights the areas of most concern to airline companies in supplier selection. Unlike many similar studies, sensitivity analysis has been performed in order to improve the robustness of the results, and to understand the importance of different criteria with respect to the selected decision.

An AHP approach in benchmarking logistics performance of the postal industry

Purpose – To develop a new benchmarking process for continuous improvement against the market leader, and report a case study in the postal industry by employing the proposed benchmarking process.Design/methodology/approach – A double AHP methodology is developed in this paper to divide benchmarking process into two main parts: performance evaluation and continuous improvement. Both qualitative and quantitative factors have been taken into consideration. The first phase aims at evaluation of the performance of the benchmarked company and its competitors. The second phase aims at finding the best practice from a list of improvement alternatives based on the first phase.Findings – The proposed framework can evaluate the performance of the case company against its competitors. It can also help the company to select the best improvement alternative for implementation in order to enhance its performance on the weakest measures.Originality/value – The proposed benchmarking process in this paper can help the cas...

A fuzzy analytic hierarchy process approach in modular product design

Product development stages. The analytic hierarchy process (AHP), which breaks down a complex problem into simple hierarchical decision-making processes, can be incorporated with fuzzy logic to suggest the relative strength of the factors in the corresponding criteria, thereby enabling the construction of a fuzzy judgement matrix to facilitate decision-making. This paper proposes a fuzzy AHP approach in modular product design complemented with a case example to validate its feasibility in a real company. Test findings indicate that the approach is helpful for providing key decision support information in terms of product module selection during product development stages. The significance of the contribution of this paper is the suggestion of a novel approach in modular product design, embracing a combination of computational intelligence and traditional techniques, thereby providing more alternatives and ideas for those researchers who are interested in this field of study.