Determining the optimal constrained multi-item (Q, r) inventory policy by maximising risk-adjusted profit

^** Email: john.betts{at}infotech.monash.edu.au^*** Email: robertj{at}unimelb.edu.au The predominant approach to determining replenishment batchsizes for capital constrained multi-item inventories is to assumethat at some point in time the replenishment of all items willcoincide, and that batch sizes are small enough that the constraintis not violated when this event occurs. However, when an inventoryconsists of a large number of independently replenished components,the probability that all replenishments coincide is very small.The standard approach thus results in unnecessarily conservativebatch sizes that under-utilise the available resource, resultingin lower profit than would be the case if a small risk of violatingthe constraint was tolerated. In this paper, a new approachto determining constrained batch sizes is presented where, fora certain average investment, the probability of exceeding abinding, or fixed, constraint on capital is determined. Thisprobability is used to define an adjustment factor to be appliedto expressions for company profit so that an optimal trade-offbetween maximising profit and reducing risk of failure is obtainedsimply by optimising this adjusted profit. By optimising profitadjusted for the risk of exceeding the constraint, the new modelyields batch sizes that are larger, and result in greater profitabilitythan those recommended under traditional models.