Title: A fuzzy EOQ model for deteriorating items with imperfect quality using proportionate discount under learning effects

Authors: Rojalin Patro; Milu Acharya; Mitali Madhusmita Nayak; Srikanta Patnaik

Addresses: Department of Mathematics, Institute of Technical Education and Research, Siksha 'O' Anusandhan University, Bhubaneswar, Odisha, India ' Department of Mathematics, Institute of Technical Education and Research, Siksha 'O' Anusandhan University, Bhubaneswar, Odisha, India ' Department of Mathematics, Institute of Technical Education and Research, Siksha 'O' Anusandhan University, Bhubaneswar, Odisha, India ' Department of Computer Science, Institute of Technical Education and Research, Siksha 'O' Anusandhan University, Bhubaneswar, Odisha, India

Abstract: The present paper analyses the impact of learning on optimal solution of inventory problems. The aim of the paper is to develop both crisp and fuzzy EOQ models for imperfect quality items under deterioration and analyse the effect of learning on holding cost, ordering cost and the number of defective items present in each lot and deal the fuzziness aspect of demand for the fuzzy model. In this paper, it is assumed that all received items are not of perfect type and after100% screening, imperfect items are dropped from the inventory and sold at an allowable proportionate discount. Due to the repetition of handling the system holding cost and ordering cost gradually decrease from one shipment to another. The optimal lot sizes of both crisp and fuzzy models are obtained by calculus method and the total profit functions for each model are also derived. The total profit function of the fuzzy model is defuzzified by using signed distance method. Numerical examples are provided to illustrate the developed models and sensitivity analysis is conducted to show the effect of number of shipments on the order quantity and the total profits of the models.

Keywords: inventory; economic order quantity; EOQ; imperfect quality; deteriorating items; proportionate discount; triangular fuzzy number; signed distance; learning effects; defuzzification.

DOI: 10.1504/IJMDM.2018.092557

International Journal of Management and Decision Making, 2018 Vol.17 No.2, pp.171 - 198

Available online: 14 Jun 2018 *

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