A Fuzzy Two-Warehouse Inventory Model of Deteriorating Items with Exponentially Demand and Backlogged Condition

Sahoo, A. K.; Indrajitsingha, Susanta Kumar; Samanta, P.; Misra, U. K.

doi:10.1007/978-981-16-1402-6_1

Cited by 1 publication

(1 citation statement)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Continuous review inventory model of deteriorating items was developed by Roy and Samanta (2009). Most of the research have been carried out in time to time on the necessity of society by Jaggi et al (2012), Ranganathan and Thirunavukarsu (2014), De and Sana (2015), Indrajitsingha et al (2019aIndrajitsingha et al ( , 2019b, Sahoo et al (2021). Kuppulakshmi et al(2023) proposed an inventory method of imperfect items in which deterioration taken as triangular fuzzy number.…”

Section: Review Of Literaturementioning

confidence: 99%

Fuzzy inventory model of seasonal deteriorating products with time and price sensitive demand and holding cost under partial backlogged

Sahu,

Ganesh,

Indrajitsingha

2024

Preprint

Self Cite

View full text Add to dashboard Cite

Demand is one of the key components of inventory modeling. Moreover, the rate of demand mostly depends upon both the time and the selling price of the product. Particularly for seasonal products like milk products and vegetables having low life time, demand depends on both production and stock. Since deterioration rate, production cost and holding-cost are uncertain in the case of seasonal products like fruits vegetable, we consider them as triangular fuzzy number. Hence in this paper, we discuss a mathematical model for deterioration of seasonal products with the demand depending upon production and selling price in crisp and fuzzy approach. In the proposed model shortages with partially backlogged is allowed. Defuzzification is done by using graded mean integration representation method. An algorithm is illustrated for the solution of problem, and for the validation of the model, a real-life numerical example is considered. Furthermore sensitivity analysis of the developed model is performed to investigate the effect of different system parameters with Mathematica 11.1 software.

show abstract