Fuzzy-Based EOQ Model With Credit Financing and Backorders Under Human Learning

Jayaswal, Mahesh Kumar; Mittal, Mandeep; Sangal, Isha; Pandey, Jayanti Tripathi

doi:10.4018/ijfsa.2021100102

Cited by 6 publications

(7 citation statements)

References 54 publications

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“…The input parameters have been taken from the Alamri et al (2022) [22], Mahata and Debnath (2022) [31] and Jayaswal et al (2021) [37]. Notations and inventory parameters with its numerical values of this model have been presented in Table 2.…”

Section: Numerical Examplementioning

confidence: 99%

A Supply Chain Model with Carbon Emissions and Preservation Technology for Deteriorating Items under Trade Credit Policy and Learning in Fuzzy

Alamri

2023

Mathematics

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In this study, a supply chain model is proposed with preservation technology under learning fuzzy theory for deteriorating items where the demand rate depends on the selling price and also treats as a triangular fuzzy number. The deterioration rate of any item cannot be eliminated due to its natural process, but it can be controlled with the help of preservation technology. Some harmful gases are emitted during the preservation process due to deteriorating items that harm the environment. In general, it can be easily seen that most of the sellers offer a trade credit policy to their regular buyers. In this paper, the retailer’s inventory stock reduces due to demand and deterioration. It is also assumed that some units are defective due to machine defects or delivery inefficiency. The retailer accepted the policy of trade credit offered by the seller. The aim of this paper is to enhance the profit of the supply chain partners. We proposed a theorem to get the optimal values of the selling price and cycle length. The retailer’s total profit is a function of selling price and cycle length, and the retailer’s total profit is optimized with respect to selling price and cycle length under trade-credit. Numerical examples are also presented for the validation of the present study, and sensitivity analysis is also discussed to know the robustness of the supply chain model. Managerial insight and observation have been given in the sensitivity section. Limitations and future work of this paper have been presented in the conclusion section.

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Section: Numerical Examplementioning

confidence: 99%

A Supply Chain Model with Carbon Emissions and Preservation Technology for Deteriorating Items under Trade Credit Policy and Learning in Fuzzy

Alamri

2023

Mathematics

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“…Kahin et al [27] developed a model with the effect of learning under the credit period policy for perishable items for imperfect quality items. Jayaswal et al [34] discussed fuzzy-based economic order quantity (EOQ) model with credit financing and backorders. Yadav et al [35] proposed an inventory model which used the game theory approach for finding the optimal ordering policy for imperfect quality items.…”

Section: Literature Review With Regard To Defective Items Inspection ...mentioning

confidence: 99%

An EOQ Model with Carbon Emissions and Inflation for Deteriorating Imperfect Quality Items under Learning Effect

et al. 2022

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We developed an economic order quantity (EOQ) model with a learning effect and carbon emissions under inflationary conditions and inspection for retailers where the items deteriorate naturally. Finally, the total profit of the retailer is maximized with respect to cycle length. A sensitivity analysis was also performed to understand the robustness of the model. In the sensitivity analysis, we discuss the impact of learning rate, inflation rate, and deterioration rate on lot size and length of the cycle, as well as the retailer’s entire profit function. Observations and managerial insights are discussed. The effect of inventory parameters on the total profit is shown in the sensitivity section.

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“…It is assumed that the demand rate is imprecise in nature but possible to explain with triangular fuzzy numbers because triangular fuzzy numbers are a good representation for the uncertain nature and also easy to handle. A triangular fuzzy number is used to model the demand function [39] which is given as…”

Section: Formulation Of Total Profit Function Under Fuzzy Environmentmentioning

confidence: 99%

Learning EOQ Model with Trade-Credit Financing Policy for Imperfect Quality Items under Cloudy Fuzzy Environment

et al. 2022

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An imprecise demand rate creates problems in profit optimization in business scenarios. The aim is to nullify the imprecise nature of the demand rate with the help of the cloudy fuzzy method. Traditionally, all items in an ordered lot are presumed to be of good quality. However, the delivered lot may contain some defective items, which may occur during production or maintenance. Inspection of an ordered lot is indispensable in most organizations and can be treated as a type of learning. The learning demonstration, a statistical development expressing declining cost, is necessary to achieve any cyclical process. Further, defective items are sold immediately after the screening process as a single lot at a discounted price, and the fraction of defective items follows an S-shaped learning curve. The trade-credit policy is adequate for suppliers and retailers to maximize their profit during business. In this paper, an inventory model is developed with learning and trade-credit policy under the cloudy fuzzy environment where the demand rate is treated as a cloudy fuzzy number. Finally, the retailer’s total profit is maximized with respect to order quantity. Sensitivity analysis is presented to estimate the robustness of the model.

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Fuzzy-Based EOQ Model With Credit Financing and Backorders Under Human Learning

Cited by 6 publications

References 54 publications

A Supply Chain Model with Carbon Emissions and Preservation Technology for Deteriorating Items under Trade Credit Policy and Learning in Fuzzy

A Supply Chain Model with Carbon Emissions and Preservation Technology for Deteriorating Items under Trade Credit Policy and Learning in Fuzzy

An EOQ Model with Carbon Emissions and Inflation for Deteriorating Imperfect Quality Items under Learning Effect

Learning EOQ Model with Trade-Credit Financing Policy for Imperfect Quality Items under Cloudy Fuzzy Environment

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