Efficiency Predictions by Fuzzy Piecewise Auto-regression in Dynamic Network System

Workshop 2015 -Advances in DEA Theory and Applications (December 1-2, 2015)Since efficiency prediction can help managers to monitor future performance and detect potential failures, it is important for production and operation management. Data envelopment analysis is comprehensively applied to evaluate the relative performance in various areas. However, only few studies try to forecast the relative performance estimated by data envelopment analysis. We propose a performance forecasting model that integrates the multi-activity dynamic network data envelopment analysis and fuzzy piecewise auto-regression. The proposed approach constructs a dynamic performance measurement with the network structure to calculate the catching-up efficiency index. The catching-up efficiency index is further decomposed into the technical efficiency change and dynamic efficiency change to capture the effect of carry-over items. The fuzzy piecewise auto-regression is applied to regress the possibility and necessity estimation models by catching-up efficiency index for forecasting efficiency. In this paper, a data from banks in Taiwan from 2006 to 2012 are applied. The results indicate that the proposed approach has highly accuracy rate.The workshop is supported by JSPS (Japan Society for the Promotion of Science), Grant-in-Aid for Scientific Research (B), #25282090, titled “Studies in Theory and Applications of DEA for Forecasting Purpose.本研究はJSPS科研費 基盤研究(B) 25282090の助成を受けたものです

An Investment Analysis for China\u27s Sustainable Development Based on Inverse Data Envelopment Analysis

In the face of environmental degradation, sustainable development has become a common goal across the globe. Making a scientifically based investment scheme is of great significance to promote the sustainable development of China\u27s economy. However, there is scarce research related to such an investment scheme of sustainable development. This paper proposes a new inverse data envelopment analysis method with undesirable outputs to make several scientifically based investment schemes from different perspectives, namely, the natural, regulation, and optimal perspectives. By this method, decision makers can scientifically forecast the specific amount of investment based on their actual sustainable development objectives, which is conducive for reducing the blindness of investment in the future. In addition, a new ideal perspective is defined to guide a definite direction for improving the level of sustainable development. Combined with the gray forecasting model GM(1,1), the methods proposed by this paper were then applied to analyze the investment problem for China\u27s sustainable development during the 2015–2024 period. The results show that: the unbalanced distribution of labor investment and the excessive investment in capital and energy are serious barriers to China\u27s sustainable development in the short term; and in the long term, the demand for investment in labor and capital will continue to increase along with a lower demand for energy investment, and that appropriately strengthening environmental regulations will not affect the overall demand for investment. Meanwhile, improvement directions for improving China\u27s sustainable development are discussed, and the results show that most of developing and undeveloped regions in China have great potential for improvement. Finally, some suggestions are proposed in order to create better conditions for China\u27s sustainable development

Using a decision-making process to evaluate efficiency and operating performance for listed semiconductor companies

Today’s high-tech industries face increasing competition and challenges. Thus, for hightech companies, making effective use of resources to enhance business performance and maintain the competitive advantage in the market has become increasingly important. Therefore, this study aimed to design a decision-making model for evaluating the efficiency and operating performance of Taiwan’s listed semiconductor companies in 2010 to provide a basis for improving business performance. In view of this, this study combines data envelopment analysis (DEA) and improved grey relational analysis (IGRA) as efficiency tools to measure relative efficiencies; the semiconductor companies are divided into two groups, efficient and inefficient. We then integrate the multiple criteria decision making (MCDM) method (e.g. VlseKriterijumska Optimizacija I Kompromisno Resenje, VIKOR), IGRA and the entropy weight method to evaluate the operating performance of the efficient and inefficient groups, respectively. Establishing a reasonable, objective and valid evaluation model to measure semiconductor companies’ operating efficiency can provide company managers, investors and policy makers with a reference for performance evaluation. First published online: 20 Jun 201

Genetic Algorithm for Solving the Integrated Production-Distribution-Direct Transportation Planning

This paper proposes a model of integrated production, distribution and transportation planning for 4-echelon supply chain system that consists of a manufacturer using a continuous production process, a distribution center, distributors and retailers. By means of time-dependent demand at all retailers and direct transportation from one echelon to its successive echelons, the purpose of this paper is to determine production/replenishment and transportation policies at manufacturer, distribution center, distributors and retailers in order to minimize annually total system cost. Due to the proposed model is classified as a mixed integer non-linear programming so it is almost impossible to solve the model using the exact optimization methods and a lot of time is needed when the enumeration methods is applied to solve only a small scale problem. In this paper, we apply the genetic algorithm for solving the model. Using integer encoding for constructing the chromosome, the best solution is going to be searched. Compared with enumeration method, the difference of the result is only 0.0594% with the consumption time is only 0.5609% time that enumeration methods need

Research in Supply Chain Management: Issue and Area Development

Today the study of supply chain management (SCM) is growing rapidly and provides a great opportunity to do research both empirical and theoretical development. Research opportunities in SCM has been reviewed by many researchers and grouped into many categories. This paper contains a review of research SCM and classify into 7 categories, namely (1) SCM Operational Management & Strategy, (2) knowledge management, (3) Relationship Management, (4) Information Technology in SCM, (5) Supply Chain Design, Logistics & Infrastructure, (6) Global Issues, (7) Environment, Legal & Regulations. The issue in each category and research opportunities will be discussed in this paper. Keywords: Supply Chain Management, Research Opportunities in SCM, Issue in SC

Air Force Institute of Technology Contributions to Air Force Research and Development, Calendar Year 1987

From the introduction:The primary mission of the Air Force Institute of Technology (AFIT) is education, but research and consulting are essential integral elements in the process. This report highlights AFIT\u27s contributions to Air Force research and development activities [in 1987]

An Integrated Framework to Assess ‘Leanness’ Performance in Distribution Centres

The theory behind lean philosophy is to create more value with less. Effective lean management enables organisations to exceed customer expectations while reducing costs. Despite the fact that numerous practices and approaches are used in the process of implementing lean philosophy and reducing waste within supply chain systems, little effort has been directed into assessing the leanness level of distribution and its impact on overall performance. Given the vital role of distribution units within supply chains, this research aims to develop a comprehensive lean assessment framework that integrates a selected set of statistical, analytical, and mathematical techniques in order to assess the ‘leanness’ level in the distribution business. Due to the limited number of published articles in the area of lean distribution, there are no clear definitions of the underlying factors and practices. Therefore, the primary phase of the proposed framework addresses the identification of lean distribution dimensional structure and practices. The other two phases of the framework discuss the development of a structured model for lean distribution and address the process to find a quantitative lean index for benchmarking lean implementation in distribution centres. Integrating the three phases provides the decision makers with an indicator of performance, subject to applying various lean practices. Incorporating the findings of a survey that sent to 700 distribution businesses in Ireland along with value stream mapping, modelling, simulation, and data envelopment analysis, has given the framework strength in the assessment of leanness. Research outcomes show that lean distribution consists of five key dimensions; workforce management, item replenishment, customers, transportation, and process quality. Lean practices associated with these dimensions are mainly focused on enhancing the communication channels with customers, simplifying the distribution networks structure, people participating in problem solving and a continuous improvement process, and increasing the reliability and efficiency of the distribution operations. The final output of the framework is two key leanness indices; one is set to measure the tactical leanness level, while the second index represents the leanness at the operational level. Both indices can effectively be used in evaluating the lean implementation process and conducting a benchmarking process based on the leanness level

Design and Management of Manufacturing Systems

Although the design and management of manufacturing systems have been explored in the literature for many years now, they still remain topical problems in the current scientific research. The changing market trends, globalization, the constant pressure to reduce production costs, and technical and technological progress make it necessary to search for new manufacturing methods and ways of organizing them, and to modify manufacturing system design paradigms. This book presents current research in different areas connected with the design and management of manufacturing systems and covers such subject areas as: methods supporting the design of manufacturing systems, methods of improving maintenance processes in companies, the design and improvement of manufacturing processes, the control of production processes in modern manufacturing systems production methods and techniques used in modern manufacturing systems and environmental aspects of production and their impact on the design and management of manufacturing systems. The wide range of research findings reported in this book confirms that the design of manufacturing systems is a complex problem and that the achievement of goals set for modern manufacturing systems requires interdisciplinary knowledge and the simultaneous design of the product, process and system, as well as the knowledge of modern manufacturing and organizational methods and techniques