Two storage inventory model with random planning horizon

Abstract

An inventory model with stock-dependent demand and two storage facilities under inflation and time value of money is developed where the planning horizon is stochastic in nature and follows exponential distribution with a known mean. The model is a order-quantity reorder-point problem where shortages are not allowed. Two rented storehouses are used for storage – one (say RW 1) at the heart of the market place and the other (say RW 2) little away from the market place. At the beginning, the item is stored at both RW 1 and RW 2. The item is sold from RW 1 and as the demand is stock-dependent, the units are continuously released from RW 2 to RW 1. Replacement of the item occurs when its inventory level reaches its reorder point ( Q r). The model is formulated to maximize the total expected proceeds out of the system from the planning horizon. A genetic algorithm (GA) is developed based on entropy theory where region of search space is gradually decreases to a small neighborhood of the optima. This is named as region reducing genetic algorithm (RRGA) and is used to solve the model. The model is illustrated with some numerical examples and some sensitivity analyses have been done.