A fuzzy inventory model with imperfect items and backorder with allowable proportionate discount

Patro, Rojalini; Acharya, Sujit; Nayak, Mitali Madhusmita; Acharya, Milu

doi:10.18280/mmc_d.390106

Cited by 2 publications

(1 citation statement)

References 21 publications

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“…Additionally, a survey conducted by Andriolo et al (2014), which examined other deterministic and stochastic EOQ models, reviewed 17 papers containing fuzzy lot-size models. Additional studies (Bakker et al, 2012;Patro et al, 2018;Patro et al, 2019;Poswal et al, 2022; are included in the papers mentioned. They checked some fuzzy inventory models considering output and degradation, separating types of inventory models, respectively, into some classifications.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Neuro-Optimization Techniques for Inventory Models in Manufacturing Sectors

Tyagi

Kumar²,

Malik

et al. 2022

JCCE

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Inventory modeling or policies are the necessity of every business or a new oil for any industry. In other words, inventory control and management are needed by businessmen or entrepreneurs to make effective strategies, i.e., for making their business profitable. It becomes a lot and a lot of vital for enterprises within the real-life things like producing sector like industry, food trade, etc. Inventory issues common in producing, remanufacturing, and lots of helpful applications like pharmaceutical. An associate improvement model for internal control of circulation enterprises was established to minimize the typical total price in the unit time of the inventory system. As we have seen, lot of researchers have made several attempts in the previous decade for improving inventory control/inventory policies, but due to the dynamic nature of human beings, it is difficult to make perfect and unique inventory for all business sectors. So, in this study, we will use collected data (from several research works done by the researchers, questionnaires, interviews) and then will apply an artificial neural network (ANN) concept to provide an optimized solution. Finally, our model shows economical, correct results, which can be additionally helpful for the inventory researchers to seek out the acceptable technique for determining the economic order quantity systems or creating AN assumption for making new inventory policies. Hence, this study provides helpful algorithms, economical inventory models for producing sectors, and future analysis direction toward our planned work.

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