Fuzzy Inventory Model for Deteriorating Items with Time-varying Demand and Shortages

Jaggi, Chandra K.; Pareek, Sarla; Sharma, Anuj Kumar; Nidhi,

doi:10.5923/j.ajor.20120206.01

Cited by 28 publications

(20 citation statements)

References 18 publications

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“…Dutta and Kumar [7] expressed a fuzzy inventory model, where the deterioration rate regarded as a fuzzy number. Fuzzy inventory model for deteriorating items with time-varying demand and shortages was developed by Jaggi et al [16], where deterioration rate and demand were reflected as a triangular fuzzy number. In our model, we represent the deterioration rate by a cloudy-fuzzy number.…”

Section: (D)mentioning

confidence: 99%

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

Barman¹,

Pervin²,

Roy³

et al. 2021

JIMO

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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.

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Section: (D)mentioning

confidence: 99%

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

Barman¹,

Pervin²,

Roy³

et al. 2021

JIMO

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show abstract

“…Jaggiet al [5] have considered fuzzy inventory model for deteriorating items with time varying demand and shortages. They developed a fuzzy economic order quantity model for deteriorating items in which demand increases with time.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy inventory model with quadratic demand, linear time dependent holding cost, constant deterioration rate and shortages

S¹,

Karthigeyan²

2020

Malaya J. Mat.

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“…Dutta and Kumar explored an optimal ordering policy for an inventory model for deteriorating items without shortage where demand rate, ordering cost and holding cost were taken as fuzzy in nature [2]. Jaggi et al introduced a fuzzy inventory model for deteriorating items with time varying demand and shortages [8]. Singh and Rathore studied an inventory model for deteriorating items with reliability consideration and trade credit [7].…”

Section: Introductionmentioning

confidence: 99%

Inventory Replenishment Policy with Time and Reliability Varying Demand

Behera¹,

Tripathy²

2018

IJSRMSS

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In real life situation, demand may be increase, decrease or constant. But, in our present study demand is assumed to be an increasing function of time which depends on reliability. Shortages are allowed and excess demand is backlogged. The economic production lot size and the reliability of the production process along with the production period are the decision variables and total cost per cycle is the objective function which is to be minimized. Further the parameters involved in the business may likely to be changed due to the fast growing marketing system. Therefore; it will be more realistic and market friendly to deal with a fuzzy model rather than a crisp model. Both crisp and fuzzy models have been proposed to determine the optimal solution. The demand, shortage cost, holding cost and deterioration rate and reliability are considered as pentagonal fuzzy numbers. Defuzzification of the total cost has been carried out by Graded Mean Representation Method and Signed Distance Method. Sensitivity analysis is also incorporated to investigate the effect of different system parameters in enhancing the cost.

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Fuzzy Inventory Model for Deteriorating Items with Time-varying Demand and Shortages

Cited by 28 publications

References 18 publications

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

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

Fuzzy inventory model with quadratic demand, linear time dependent holding cost, constant deterioration rate and shortages

Inventory Replenishment Policy with Time and Reliability Varying Demand

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