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Fuzzy set theory applications in production management research: a literature survey

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TLDR
This paper provides a survey of the application of fuzzy set theory in production management research, and identifies selected bibliographies on fuzzy sets and applications.
Abstract
Fuzzy set theory has been used to model systems that are hard to define precisely. As a methodology, fuzzy set theory incorporates imprecision and subjectivity into the model formulation and solution process. Fuzzy set theory represents an attractive tool to aid research in production management when the dynamics of the production environment limit the specification of model objectives, constraints and the precise measurement of model parameters. This paper provides a survey of the application of fuzzy set theory in production management research. The literature review that we compiled consists of 73 journal articles and nine books. A classification scheme for fuzzy applications in production management research is defined. We also identify selected bibliographies on fuzzy sets and applications.

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Citations
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Journal ArticleDOI

Fuzzy scheduling: Modelling flexible constraints vs. coping with incomplete knowledge

TL;DR: An overview of some fuzzy set-based approaches to scheduling is proposed,phasizing two distinct uses of fuzzy sets: representing preference profiles and modelling uncertainty distributions, and a possibility-theoretic counterpart of PERT.
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Facility location selection using fuzzy topsis under group decisions

TL;DR: This work presents a fuzzy TOPSIS model under group decisions for solving the facility location selection problem, where the ratings of various alternative locations under different subjective attributes and the importance weights of all attributes are assessed in linguistic values represented by fuzzy numbers.
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A review of the extensions of a modified EOQ model for imperfect quality items

TL;DR: The current body of research that has extended the Salameh and Jaber (2000) EOQ model for imperfect items, and the impact of human error on production and inventory systems is summarized.
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Material Requirement Planning with fuzzy constraints and fuzzy coefficients

TL;DR: A new fuzzy mathematical programming model for production planning under uncertainty in an industrial environment that considers fuzzy constraints related to the total costs, the market demand and the available capacity and fuzzy coefficients for the costs due to the backlog of demand and for the required capacity.
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A comprehensive survey and future trend of simulation study on FMS scheduling

TL;DR: The objective of this paper is to review scheduling study on FMSs and analyse future trend that employed simulation techniques as the analyzing tool and conclude that AI approaches will be dominating in future study.
References
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Journal ArticleDOI

Fuzzy-set theoretic interpretation of economic order quantity

K. S. Park
TL;DR: The EOQ formula is reexamined in a fuzzy-set-theoretic perspective in view of the inherently fuzzy aspect of the cost determination.
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A comparison of fuzzy forecasting and Markov modeling

TL;DR: These models are compared with each other and with a time-invariant Markov model using linguistic labels with probability distributions and compared with three traditional time series models, a first-order autoregressive (AR) model and two second-order auto-regressive (AR(2) models, all of which are time- Invariant.
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The use of fuzzy variables in pert

TL;DR: A method for estimating a project completion time in the situation when activity duration times in the project network model are given in the form of fuzzy variables—fuzzy sets on time space is presented.
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Applications of fuzzy set theory

TL;DR: It is demonstrated that fuzzy set theory is applicable to a wide range of practical problems and that simple fuzzy control algorithms do give good results.