Learning-based inventory model for deteriorating imperfect quality items under inflation

Abstract

Nowadays, the inspection process plays a vital role to improve the quality of items. Despite efficient planning, there may be some defective items delivered to the retailer in the delivered lot. Moreover, in today's unstable global economy, there is a consequent decline in the real value of money because the general level of prices of goods and services is rising, also known as inflation. In the past several years, most countries have suffered from large-scale inflation and a sharp decline in the purchasing power of money. The present paper contributes to a set of models capturing economic order quantity (EOQ) with a learning effect for decaying defective items under the inflationary condition. The objective of this paper is to determine the impact of learning on the optimal order quantity and corresponding total profit under inflationary conditions. An expression for the total profit of the retailer has been optimised with respect to cycle length. Conclusively, sensitive analysis has been presented as a consequence of numerical examples.