THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Preface. Automatic Train Operation System by Predictive Fuzzy Control (S. Yasunobu, S. Miyamoto). Application of Fuzzy Reasoning to the Water Purification Process (O. Yagashita, O. Itoh, M. Sugeno). The Application of a Fuzzy Controller to the Control of a Multi-Degree-of-Freedom Robot Arm (E.M. Scharf, N.J. Mandic). Optimizing Control of a Diesel Engine (Y. Murayama et al.). Development of Performance Adaptive Fuzzy Controllers with Application to Continuous Casting Plants (G. Bartolini et al.). A Fuzzy Logic Controller for Aircraft Flight Control (L.I. Larkin). Automobile Speed Control System Using a Fuzzy Logic Controller (S. Murakami, M. Maeda). An Experimental Study on Fuzzy Parking Control Using a Model Car (M. Sugeno, K. Murakami). A Fuzzy Controller in Turning Process Automation (Y. Sakai, K. Ohkusa). Design of Fuzzy Control Algorithms with the Aid of Fuzzy Models (W. Pedrycz). Human Operator's Fuzzy Model in Man-Machine System with a Nonlinear Controlled Object (K. Matsushima, H. Sugiyama). The Influence of Some Parameters on the Accuracy of a Fuzzy Model (J.B. Kiszka, M.E. Kochanska, D.S. Sliwinska). A Microprocessor Based Fuzzy Controller for Industrial Purposes (T. Yamazaki, M. Sugeno). The Application of Fuzzy and Artificial Intelligence Methods in the Building of a Blast Furnace Smelting Process Model (H. Zhao, M. Ma). An Annotated Bibliography of Fuzzy Control (R.M. Tong).

Industrial applications of fuzzy control

https://ir.nctu.edu.tw:443/bitstream/11536/100881/1/982410H009004.PDF

國際期刊 Transportation Research-Part E---Logistics and Transportation Review 特刊編輯補助

Supply chain risk management (SCRM) encompasses a wide variety of strategies aiming to identify, assess, mitigate and monitor unexpected events or conditions which might have an impact, mostly adve...

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Supply chain risk management and artificial intelligence: state of the art and future research directions

A supervised machine learning approach to data-driven simulation of resilient supplier selection in digital manufacturing

The aim of this paper is to review the literature in the field of supplier selection under supply chain risk management. Collected papers from 2003 to 2014 are analyzed and classified, first, according to the characteristics of the problem they deal with, secondly, according to the approach they propose, and thirdly, according to the techniques they use. The papers have been grouped into five categories: the first group relates to quantitative approaches to supplier selection, the second concerns qualitative approaches, the third consists of hybrid approaches that blend two or more different approaches together, the fourth relates to simulation approaches and the last group to artificial intelligence. The techniques used in each category are outlined. The different approaches and their associated techniques are analyzed and some recommendations are made on improving their efficiency and performance. This paper is thus a systematic scope review of journal articles and conference papers issued during this period. It brings together a collection of 124 papers on the topic of supplier selection under supply chain risk management.

Optimization of a supply portfolio in the context of supply chain risk management: literature review

This paper studies the problem of supplier selection and order allocation in a retail supply chain (comprising suppliers, a central purchasing unit and outlets) under disruption risk. The final demand is deterministic. Suppliers are located in different geographic areas, and supplies are subject to a positive probability of disruption. Different capacity and failure probabilities for each supplier are considered. Our analysis focuses on the insurance versus profitability trade-off faced by a supply manager who buys from suppliers for the outlets. Instead of determining optimal decisions given an objective function and the risk sensitivity of the decision-maker, we use a mixed integer linear programming approach to provide decision-making support that shows a supply manager the ‘elasticity of (expected) losses versus (expected) profits’. Under this model, and depending on the profit-and-loss targets, a supply manager of known risk sensitivity (i.e. risk aversion and loss aversion) can make better decisions...

Supplier selection under risk of delivery failure: a decision-support model considering managers’ risk sensitivity

This paper presents a new extension of SALBP-2, so called assembly line resource assignment and balancing problem of type 2 (ALRABP-2). Two main differences from the existing literature are revealed in this work. The first is on the objective function which is a multiple one. It is aimed here to minimize both the cycle time and the cost per time unit (hour) of a line for a fixed number of stations to satisfy the constraints of precedence between tasks and compatibility between resources. The second difference lies in the proposed method to solve this problem. A new version of multi-objective genetic algorithm (MOGA) called hybrid MOGA (HMOGA) is elaborated. Full experiment design is used to obtain a better MOGA parameters combination. The effectiveness of the HMOGA was assessed through a set of literature problems. The performance of HMOGA shows a good quality of the fronts generated and a better problem-solving capacity for two optimisations.

A multi-objective genetic algorithm for assembly line resource assignment and balancing problem of type 2 (ALRABP-2)

In this paper, a multi-objective, multi-product, multi-period production and transportation planning problem in the context of a multi-site supply chain is proposed. The developed model attempts simultaneously to maximize the profit and to maximize the product quality level. The objective of this paper is to provide the decision maker with a front of Pareto optimal solutions and to help him to select the best Pareto solution. To do so, the epsilon-constraint method is adopted to generate the set of Pareto optimal solutions. Then, the technique for order preference by similarity to ideal solution (TOSIS) is used to choose the best compromise solution. The multi-criteria optimization and compromise solution (VIKOR), a commonly used method in multiple criteria analysis, is applied in order to evaluate the selected solutions using TOPSIS method. This paper offers a numerical example to illustrate the solution approach and to compare the obtained results using TOSIS and VIKOR methods.

Faouzi Masmoudi

Papers

Optimization of a supply portfolio in the context of supply chain risk management: literature review

Supplier selection under risk of delivery failure: a decision-support model considering managers’ risk sensitivity

A multi-objective genetic algorithm for assembly line resource assignment and balancing problem of type 2 (ALRABP-2)

Pareto Optimal Solution Selection for a Multi-Site Supply Chain Planning Problem Using the VIKOR and TOPSIS Methods

Multi-objective stochastic multi-site supply chain planning under demand uncertainty considering downside risk