A fuzzy random EPQ model for imperfect quality items with possibility and necessity constraints

Kumar, Ravi Shankar; Goswami, Adrijit

doi:10.1016/j.asoc.2015.05.024

Cited by 30 publications

(10 citation statements)

References 46 publications

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“…They assumed that due to this production process not remain perfect. Kumar and Goswami [20] proposed a particle swarm optimization technique to obtain the optimal value of production run time for imperfect production system. They considered demand rate as random variable to incorporate the stochastic variability in it.…”

Section: Introductionmentioning

confidence: 99%

An EPQ model with two-level trade credit and multivariate demand incorporating the effect of system improvement and preservation technology

Kumar¹,

Kumar²,

Kumari³

2021

Malaya J. Mat.

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Nowadays every decision-maker from production industries is more concern with the system improvement. They also focused in adopting different marketing strategies to make their production system as successful system. In the current study, a production quantity model is explored for deteriorating item by considering volume flexibility. Multivariate demand is considered in the model which is the function of promotional efforts, selling price, and credit period. An additional investment is made by the decision-maker to improve the system quality and reduce the deterioration rate. Whole of the analysis is carried out under the effect of inflation. Profit function of the current study is nonlinear so a search algorithm is suggested to obtain the optimal values of selling price, production time, and production rate. At the end, numerical analysis along with sensitivity is executed to validate the model and to observe the effect of different parameters on the optimal solution of the problem.

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Section: Introductionmentioning

confidence: 99%

An EPQ model with two-level trade credit and multivariate demand incorporating the effect of system improvement and preservation technology

Kumar¹,

Kumar²,

Kumari³

2021

Malaya J. Mat.

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“…Das et al [29] presented an integrated production inventory model in interactive fuzzy credit period for deteriorating items. Kumar and Goswami [30] proposed a fuzzy random EPQ model for imperfect quality items with possibility and necessity constraints. Recently, Mahata [31] investigated the learning effect on inventory modelling.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive study of an economic order quantity model under fuzzy monsoon demand

Mahata

2019

Sādhanā

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This article deals with a classical economic order quantity (EOQ) model under monsoon type fuzzy demand rate. It is nothing but the generalization of cloudy fuzzy model. We split the EOQ model into three parts according to the real-time fuzzy components of the demand rate. To defuzzify the model we develop an algorithm and the solution is obtained with the help of a nonlinear optimization technique that requires maximum aspiration level of the fuzzy membership of the objective function. Moreover, for comparative study we take numerical results of the crisp, general fuzzy and cloudy fuzzy model also. By this study we have shown that the decision maker might have to choose the monsoon type fuzzy environment all the time to control the proposed inventory. Moreover, sensitivity analysis and graphical illustrations are made to justify the new fuzzy approach. adhana(0123456789().,-volV)FT3 ](0123456789().,-volV)

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“…Numerous articles have been found in fuzzy system. Some notable recent works in fuzzy system are discussed as follows: Kumar and Goswami [34,35] proposed a fuzzy random EPQ model for imperfect quality items with possibility and necessity constraints. Mahata [36] investigated the learning effect of the unit production time on optimal lot size for the imperfect production process with partial backlogging of shortage quantity in fuzzy random environments.…”

Section: Introductionmentioning

confidence: 99%

An EPQ model for three-layer supply chain with partial backordering and disruption: Triangular dense fuzzy lock set approach

Mahata

2019

Sādhanā

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This article deals with three-echelon supply chain (SC) network involving flow of raw materials with imperfect quality, the manufacturer and multiple retailers under the effect of learning experiences in fuzzy decision-making process. Existing literature explores the SC model under full backordering and disruption. Thus, in this study we first develop a production-inventory control problem accompanied with partial backlogging and random disruptions. Any batch received from the supplier is inspected by the manufacturer and if any of them are found to be flawed then all the goods in the inspected batch are rejected. However, we present a case study for problem definition and to comprehend the model into practical applicability. To minimize the aggregate cost of the SC we have utilized the Triangular dense fuzzy lock set for controlling the cost vector of the proposed objective function of the model. Utilizing new defuzzification method and applying the proper keys, chosen by the decision maker, it is possible to minimize the average system cost exclusively. Finally, graphical illustrations and sensitivity analysis are made to justify the model.

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A fuzzy random EPQ model for imperfect quality items with possibility and necessity constraints

Cited by 30 publications

References 46 publications

An EPQ model with two-level trade credit and multivariate demand incorporating the effect of system improvement and preservation technology

An EPQ model with two-level trade credit and multivariate demand incorporating the effect of system improvement and preservation technology

A comprehensive study of an economic order quantity model under fuzzy monsoon demand

An EPQ model for three-layer supply chain with partial backordering and disruption: Triangular dense fuzzy lock set approach

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