An inventory model for deteriorating items with partial backlogging using linear demand in fuzzy environment

Kumar, Neeraj; Kumar, Sanjey

doi:10.1080/23311975.2017.1307687

Cited by 9 publications

(4 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Carbon emission may be introduced into our advanced model as well. In the future, we can apply the "sign distance" method [23] in our model to defuzzify the fuzzy objective function. Eventually, our model could become the basis of an attractive research direction, where researchers can replace the demand rate by carbon-concerned demand rate, and they can consider imperfect quality deteriorating items, too.…”

Section: Discussion Ofmentioning

confidence: 99%

Back-ordered inventory model with inflation in a cloudy-fuzzy environment

Barman¹,

Pervin²,

Roy³

et al. 2021

JIMO

View full text Add to dashboard Cite

In this paper, an Economic Production Quantity model for deteriorating items with time-dependent demand and shortages including partially back-ordered is developed under a cloudy-fuzzy environment. At first, we develop a crisp model by considering linearly time-dependent demand with constant deterioration rate, constant inflation rate and shortages under partially back-ordered, then we fuzzify the model to archive a decision under the cloudy-fuzzy (extension of fuzziness) demand rate, inflation rate, deterioration rate and the partially back-ordered rate which are followed by their practical applications. In this model, we assume ambiances where cloudy normalized triangular fuzzy number is used to handle the uncertainty in information which is coming from the data. The main purpose of our study is to defuzzify the total inventory cost by applying Ranking Index method of fuzzy numbers as well as cloudy-fuzzy numbers and minimize the total inventory cost of crisp, fuzzy, and cloudy-fuzzy model. Finally, a comparative analysis among crisp, fuzzy and cloudy-fuzzy total cost is carried out in this paper. Numerical example, sensitivity analysis, and managerial insights are elaborated to justify the usefulness of the new approach. A comparative inquiry of the numerical result with a new existing paper is also carried out. This paper ends with a conclusion along with advantages and limitations of our solution approach, and an outlook towards possible future studies.

show abstract

Section: Discussion Ofmentioning

confidence: 99%

Back-ordered inventory model with inflation in a cloudy-fuzzy environment

Barman¹,

Pervin²,

Roy³

et al. 2021

JIMO

View full text Add to dashboard Cite

show abstract

“…An effective inventory system is made of many features such as simplified implementation, service quality and cost-effectiveness (Kumur and Kumar, 2017). Sekar and Uthayakumar (2018) developed a production inventory model for a single vendor and single buyer integrated demand with multiple production setups and rework.…”

Section: Literature Reviewmentioning

confidence: 99%

A Framework for Intelligent Inventory Prediction in Small and Medium- Scale Enterprise

2021

EJBM

View full text Add to dashboard Cite

The aim of this research is to apply an intelligent technique to predict optimal inventory quantity in small and medium-scale enterprise. This is in view of the fact that the conventional models such as the EOQ model use only deterministic while some decision variables are non-deterministic in nature. Forecasted average demand of items for ten months in a small-scale retail outlet was collected and trained using an Artificial Neural Networks (ANN) of 5 neurons in the input layer with eight neurons in the first hidden layer and four neurons in the second hidden layer. Two feed-forward training algorithms of quasi-newton and quick propagation were employed in the training with the results of fuzzy logic technology found in the literature as the target output. Results obtained show that the quasi-newton algorithm covaries stronger with the fuzzy logic results than the quick propagation results. The objective and subjective feelings of the inventory manager were also captured to optimise the results of the training.The study is at a framework stage and will proceed to implementation level when more datasets are collected. Data collection in a small-scale outlet is a daunting task as record keeping is hardly done. The inclusion of nondeterministic circumstances such as emotional and objective feelings of the inventory manager to predict inventory is novel considering the fact that studies in the available intelligent inventory prediction have not employed such variables in their predictions.

show abstract

“…As a result, Kumar, N., and Kumar, S. [3] proposed an inventory model for decaying products that included the effects of learning and salvage value. Kumars, N. and S. [4] DOI: 10.1002/masy. 202200116 A linear variant of the life cycle can be used to estimate the demand rate in a fuzzy situation.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, Kumar, N., and Kumar, S. [ 3 ] proposed an inventory model for decaying products that included the effects of learning and salvage value. Kumars, N. and S. [ 4 ]…”

Section: Introductionmentioning

confidence: 99%

Materials under Inflation: An Optimal Supply Policy Model

Arora

Gupta

Srivastav

2023

Macromolecular Symposia

View full text Add to dashboard Cite

The continuous analysis model is extended in this paper to allow cost and demand values to be computed by a time-lapse log concave function that meets network criteria for materials. Failure costs, insufficient maintenance costs, and replenishment costs are all deemed lower than capital costs, depending on the size of the lot for materials. Damage occurs at a degree that is independent of time. A backlog phase is allowed in the model. The backlog is being reduced at a steady pace. In this scenario, results that confirm the existence of an optimal policy and a testing algorithm are demonstrated. The survey system's overall cost is also demonstrated to be proportional to the number of refills. As a result, the ideal number of refills is determined using a solution method. The result is verified with the help of a numerical example.

show abstract

An inventory model for deteriorating items with partial backlogging using linear demand in fuzzy environment

Cited by 9 publications

References 21 publications

Back-ordered inventory model with inflation in a cloudy-fuzzy environment

Back-ordered inventory model with inflation in a cloudy-fuzzy environment

A Framework for Intelligent Inventory Prediction in Small and Medium- Scale Enterprise

Materials under Inflation: An Optimal Supply Policy Model

Contact Info

Product

Resources

About