This article examines a two-commodity continuous review perishable inventory system. The demands are arrived at for each product by independent Markovian arrival processes (MAP). Lifetimes follow an exponential distribution. commodities assumed to be substitutable. If both have reached zero, demand is backlogged up predetermined levels. article’s novelty has been local purchase, which made clea...

We propose an approximation scheme for two important but difficult single-product inventory systems, specifically, the lost-sales system and the perishable product system. The approach is based on quadratic approximations of cost-to-go functions within the framework of Approximate Dynamic Programming via Linear Programming. We propose heuristics and evaluate their performance against existing h...

The objective of this model is to investigate the inventory system for perishable items with linear demand pattern where Weibull deterioration is considered. The Economic order quantity is determined for minimizing the average total cost per unit time. The unit production cost is taken to be inversely related to the demand rate. The result is illustrated with numerical example.

A retailer is endowed with a finite inventory of a non-perishable product. Demand for this product is driven by a price-sensitive Poisson process that depends on an unknown parameter, θ; a proxy for the market size. If θ is high then the retailer can take advantage of a large market charging premium prices, but if θ is small then price markdowns can be applied to encourage sales. The retailer h...

The present work deals with the supply chain problems related to perishable products. The EOQ model has been used to analyze the data collected and suggest a ordering policy that will minimize the loses and maximize the organizational value. The work provides a suggestion for managers to take decision regarding use of self space and reordering of items depending on the inventory usage.

We formulate the multiperiod, distribution-free perishable inventory problem as a problem of prediction with expert advice and apply an online learning method (the Weak Aggregating Algorithm) to solve it. We show that the asymptotic average performance of this method is as good as that of any time-dependent stocking rule in a given parametric class.