Smooth Priorities for Multi-Product Inventory Control

Abstract

Whenever dealing with periodic review multi-products inventory control for capacitated machines, one of the main issues that has to be addressed concerns the dynamic capacity allocation. That is, how to assign capacity to the several competing products that require more than it is available. One typical approach is to assign priorities to the products, according to some degree of relative importance. Whereas priority based capacity allocation is attractive, due to its simplicity and for the fact that it makes sense in a significant number of settings, we contend this to be too unfair to lower priority products, given their access to production tends to be highly variable and uncertain. Departing from what we call strict priorities, we propose a priority based mechanism that improves on this drawback, termed smooth priorities. This new policy for multi-product, limited capacity production systems with stochastic demand is studied. Theoretical comparisons are made to the common policies of strict priorities and linear scaling. An optimizer based on Infinitesimal Perturbation Analysis, IPA, simulation is devised and results of practical comparison between smooth and strict priorities are presented. The structure of the cost function with smooth priorities is studied through function plots obtained from simulation and numerical results show consistent better performances than those achieved under strict priorities.