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A Stochastic Model for Inventory Cost Calculation with Fuzzy Demand


Affiliations
1 Dept. of Industrial Engg. & Management, Siddaganga Institute of Technology, Tumkur, India
2 Dept. of Studies in Mechanical Engg., University BDT College of Engg., Davangere, India
3 VIT University, Vellore, India
     

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In the traditional inventory systems, demand and lead time data are assumed to be available and follow some probability distribution mostly normal. But in reality supply chain is dynamic in nature and associated with lots of uncertainties. In this paper an attempt is made to model (Q,r) (optimum order quantity, reorder point) policy in uncertain supply chain environment. Imprecise demand is modeled using fuzzy set theory and an iterative procedure is developed to calculate optimum order quantity, reorder point and total cost of maintaining inventory. The iterative procedure is demonstrated using a numerical example and obtained numerical results are compared with their crisp counterpart.

Keywords

Continuous Review, (Q,R) Policy, Fuzzy Demand, Triangular Fuzzy Number, Extension Principle.
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  • A Stochastic Model for Inventory Cost Calculation with Fuzzy Demand

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Authors

B. Latha Shankar
Dept. of Industrial Engg. & Management, Siddaganga Institute of Technology, Tumkur, India
S. Basavarajappa
Dept. of Studies in Mechanical Engg., University BDT College of Engg., Davangere, India
Rajeshwar S. Kadadevaramath
Dept. of Industrial Engg. & Management, Siddaganga Institute of Technology, Tumkur, India
R. Vezhavendhan
VIT University, Vellore, India

Abstract


In the traditional inventory systems, demand and lead time data are assumed to be available and follow some probability distribution mostly normal. But in reality supply chain is dynamic in nature and associated with lots of uncertainties. In this paper an attempt is made to model (Q,r) (optimum order quantity, reorder point) policy in uncertain supply chain environment. Imprecise demand is modeled using fuzzy set theory and an iterative procedure is developed to calculate optimum order quantity, reorder point and total cost of maintaining inventory. The iterative procedure is demonstrated using a numerical example and obtained numerical results are compared with their crisp counterpart.

Keywords


Continuous Review, (Q,R) Policy, Fuzzy Demand, Triangular Fuzzy Number, Extension Principle.