Optimization of fuzzy inventory model under fuzzy demand and fuzzy lead time using Exponential fuzzy number

De, Pijus Kanti; Rawat, Apurva

doi:10.1109/fskd.2012.6234310

Cited by 3 publications

(1 citation statement)

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“…Chen and Li (2000) introduced the method to treat the defuzzification, ranking and distance of fuzzy number with exponential membership function by modified concept of graded mean integration representation method. De and Rawat (2012) reported that a realistic inventory model with demand per day items and the lead time for the order of the items are imprecise and non-linear in nature, and are can be characterized by exponential fuzzy numbers.…”

Section: Introductionmentioning

confidence: 99%

System reliability for non-repairable multi-state series–parallel system using fuzzy Bayesian inference based on prior interval probabilities

Bamrungsetthapong

Pongpullponsak

2014

International Journal of General Systems

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In this article, the fuzzy concepts are applied in analysis of the system reliability problem. The fuzzy number is used to construct the fuzzy reliability of the non-repairable multi-state series-parallel system (NMSS). The fuzzy failure rate function is represented by an exponential fuzzy number. By using this innovative approach, the fuzzy system reliability of NMSS is created. In order to analyse this fuzzy system reliability, the fuzzy Bayesian point estimate of fuzzy system reliability is made by the conventional Bayesian formula. And, the posterior fuzzy system reliability of NMSS is developed by Bayesian inference with fuzzy probabilities. Finally, the performance of the method is measured by the mean square error of fuzzy Bayesian point estimate for the fuzzy system reliability of NMSS.

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Section: Introductionmentioning

confidence: 99%