[서평]「The Unified Modeling Language User Guide」

8. Subset Selection in Regression (Monographs on Statistics and Applied Probability, no. 40). By A. J. Miller. ISBN 0 412 35380 6. Chapman and Hall, London, 1990. 240 pp. £25.00.

Subset Selection in Regression

The notion of fuzziness as defined in this paper relates to situations in which the source of imprecision is not a random variable or a stochastic process, but rather a class or classes which do not possess sharply defined boundaries, e.g., the “class of bald men,” or the “class of numbers which are much greater than 10,” or the “class of adaptive systems,” etc. A basic concept which makes it possible to treat fuzziness in a quantitative manner is that of a fuzzy set, that is, a class in which there may be grades of membership intermediate between full membership and non-membership. Thus, a fuzzy set is characterized by a membership function which assigns to each object its grade of membership (a number lying between 0 and 1) in the fuzzy set. After a review of some of the relevant properties of fuzzy sets, the notions of a fuzzy system and a fuzzy class of systems are introduced and briefly analyzed. The paper closes with a section dealing with optimization under fuzzy constraints in which an approach to...

Fuzzy sets and systems

Economic systems are increasingly prone to complexity and uncertainty. Therefore, making well-informed decisions requires risk analysis, control and mitigation. In some areas such as finance, insurance, crisis management and health care, the importance of considering risk is largely acknowledged and well-elaborated, yet rather heterogeneous concepts and approaches for risk management have been developed. The increased frequency and the severe consequences of past supply chain disruptions have resulted in an increasing interest in risk. This development has led to the adoption of the risk concepts, terminologies and methods from related fields. In this paper, existing approaches for quantitative supply chain risk management are reviewed by setting the focus on the definition of supply chain risk and related concepts.

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A critical review on supply chain risk – Definition, measure and modeling ☆

The management of food distribution networks is receiving more and more attention, both in practice and in the scientific literature. In this paper, we review quantitative operations management approaches to food distribution management, and relate this to challenges faced by the industry. Here, our main focus is on three aspects: food quality, food safety, and sustainability. We discuss the literature on three decision levels: strategic network design, tactical network planning, and operational transportation planning. For each of these, we survey the research contributions, discuss the state of the art, and identify challenges for future research.

https://mediatum.ub.tum.de/doc/1165266/file.pdf

Quality, safety and sustainability in food distribution : A review of quantitative operations management approaches and challenges

Mathematical programming models for supply chain production and transport planning

Managing uncertainty is a main challenge within supply chain management. Therefore, it is expected that those supply chain planning methods which do not include uncertainty obtain inferior results if compared with models that formalise it implicitly. This article presents a review of the literature related to supply chain planning methods under uncertainty. The main objective is to provide the reader with a starting point for modelling supply chain under uncertainty applying quantitative approaches. We have defined a taxonomy to classify models from 103 bibliographic references dated 1988–2007. Finally, some conclusions about the works analysed have been drawn and future lines of research have been identified.

David Peidro

Papers

Mathematical programming models for supply chain production and transport planning

Quantitative models for supply chain planning under uncertainty: a review

Fuzzy optimization for supply chain planning under supply, demand and process uncertainties

A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment

The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand