A Sustainable Inventory Model with Advertisement Effort for Imperfect Quality Items under Learning in Fuzzy Monsoon Demand

In this paper, we proposed a sustainable inventory model with a learning effect for imperfect quality items under different kinds of fuzzy environments like crisp, general fuzzy, cloudy fuzzy, and monsoon fuzzy. We divided the mathematical model into three parts under the learning effect according t...

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Bibliographic Details
Published inMathematics (Basel) Vol. 12; no. 15; p. 2432
Main Authors Alamri, Osama Abdulaziz, Lamba, Navneet Kumar, Jayaswal, Mahesh Kumar, Mittal, Mandeep
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.08.2024
Subjects
advertisement effort
Advertising
Algorithms
Analysis
carbon emissions
Commodities
Cost analysis
Credit policy
Decision making
Discount rates
Forecasts and trends
Fuzzy logic
Fuzzy sets
Impact analysis
Inventory
Inventory control
Inventory management
Learning
Literature reviews
Mathematical models
Mathematical optimization
monsoon fuzzy environment
Monsoons
Order quantity
Parameter sensitivity
Real time
screening process
Sensitivity analysis
Set theory
Supply chains
waste management policy
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Summary:In this paper, we proposed a sustainable inventory model with a learning effect for imperfect quality items under different kinds of fuzzy environments like crisp, general fuzzy, cloudy fuzzy, and monsoon fuzzy. We divided the mathematical model into three parts under the learning effect according to the real-time fuzzy components (crisp, cloudy, and monsoon environments) of the demand rate of the items. We minimized the total inventory cost with respect to cycle length in each environment under the proposed assumptions. The non-linear optimization technique is applied for the algorithm and the solution method to find the decision variable. Finally, we compared the total inventory cost under different fuzzy environments and our finding is that the fuzzy monsoon environment is a more effective fuzzy environment than crisp and cloudy fuzzy environments. We have presented a numerical example for the validation of the proposed model and have shown the impact of the inventory input parameters on the cycle length and total inventory fuzzy cost. The managerial insights and future scope of this proposed study have been shown in the sensitivity analysis and conclusion. The limitations, application, future extension and scope, and social implementation have been shown in this research study.
ISSN:2227-7390
2227-7390
DOI:10.3390/math12152432