Fuzzy rough supply chain model under inflation and credit period with stock dependent consumption rate and partial backlogging shortages via genetic algorithm. (2015)

• Record Type: Journal Article
• Authors: Jana, Dipak Kumar; Das, Barun; Maity, Kalipada
• Is Part Of: International journal of computing science and mathematics. Volume 6:Number 6(2015)
• Page Start: 555
• Page End: 580
• Publication Date: 2015
• Subjects: fuzzy sets -- fuzzy logic -- rough sets -- inventory modelling -- money time value -- delayed payment -- genetic algorithms -- supply chain management -- SCM -- inflation -- credit period -- stock dependent consumption rate -- partial backlogging -- shortages -- ordering policy -- deteriorating items -- discount rates -- order quantity; Mathematics -- Periodicals; Computer science -- Periodicals; Mathematics -- Data processing -- Periodicals; 510.285
• Languages: English
• ISSNs: 1752-5055

Abstract

In many inventory situations, purchasers are allowed a period to pay back for the goods bought without paying any interest. Depending on the length of that payment period, the purchaser can earn interest on the sales of the inventory. This paper develops a model to determine an optimal ordering policy for deteriorating items under inflation, stock dependent demand, permissible delay of payment, allowable shortage and unfinished demand is partially backlogged in fuzzy rough environments. The present value of total cost incurred in this inventory system is developed first, then an optimal order quantity and maximum allowable shortage are obtained by using a search procedure. The effect of inflation and time value of money was investigated under given sets of inflation and discount rates. This study shows that the optimal order quantity and maximum allowable shortage vary with the difference between inflation and time discount. Computational results provide some interesting policy implications. The genetic algorithm (GA) is used to make decision for above inventory model. The model is illustrated with some numerical data.