Inventory Rules Research Articles

Optimal Inventory Rule for a Linear Trend in Demand with a Constant Replenishment Period

Optimal Inventory Rule for a Linear Trend in Demand with a Constant Replenishment Period

Performance of Lot-Sizing Rules In an MRP System With Different Operating Conditions

In this paper we report the results of analyses which indicate that traditional thought on the relationship between stockout frequency, inventory level, capacity level, and inventory rules should be re-examined. A significant finding is that lot-sizing rules can affect aggregate plans as they relate to capacity requirements.

EPA plans seminars on TSCA inventory rules

EPA plans seminars on TSCA inventory rules

Time Delay Effects in Computerised Physical Distribution Systems

Computerising inventory control procedures is usually an attempt to gain better control over stock availability. The effectiveness of the procedures depends on the time delays imparted by such events as order processing and delivery. Through these time delays, much of a finished goods physical distribution system is linked together through the inventory control procedures. Changing the length of any one time element through changes in inventory stocking rules, order processing methods or selected transportation services impacts on the economics of the entire physical distribution system. Little is understood about the effects of time change in such complex systems. In this article, the actual computer inventory control procedures of a chemical company were computer simulated. Physical distribution system design decisions and their associated time delay effects were explored by interrogating the model. Surprising effects were discovered, some of them being counter‐intuitive to what simple theory would predict. Management guidelines were provided as to the system‐wide economic consequences of change in individual elements of a physical distribution system.

Problems Involving Infrequent but Significant Contingencies

Problematic situations often arise in which it is required to provide a solution which will tend to avoid events, which, if they occur, would be very costly, or, if not directly costable, they would be highly undesirable. Although direct approaches to this sort of problem exist, they can be unmanageable. If, however, we take as a posit, that the frequency with which the undesirable events arise, in the optimum solution, is small, considerable simplifications can be made. Naturally we need to check the posit once the solution has been found. This paper considers three applications of this principle, viz. determination of how many chargers are needed for steel furnaces, where the undesirable event is “a furnace waits for service”; determination of the number of emergency beds to set aside in a hospital unit, where the undesirable event is “an emergency case arrives and no bed is immediately available”; determination of an inventory reorder rule where the undesirable event is “stock run-out”. The general principle is formalized.

Personality test interpretation by digital computer.

In this study a set of decision rules was devised for interpreting profile patterns of the Minnesota Multiphasic Personality Inventory (MMPI) of maladjusted and adjusted college students. The procedure used was that of computer programming of the "maladjusted" versus "adjusted" decisions of an expert test interpreter. The interpreter's decision-making processes were tape-recorded while he was thinking aloud during the sorting of the profiles of 126 college students. The programmed decision rules, which were based on the interpreter's protocol and which were improved upon by a process of trial-and-error statistical checking, yielded a greater hit percentage than the decisions of the original interpreter. In its final form, the set of objective configural inventory rules identified correctly large numbers of maladjusted college students in two cross-validation samples.

Constrained Inventory Rules for Production Smoothing

Production smoothing (or production planning) methods are used to decide on aggregate production levels for a factory, without specifying what individual products should be produced, or when, or how much. Inventory control of finished goods inventory makes these latter decisions, but does so for each product, independently, without regard for the aggregate effect on the factory. This paper discusses several (unsatisfactory) attempts to make these two sets of decisions consistent, and then presents several ways of making trigger and lot-size inventory decisions (production decisions for individual products) that aim at minimizing total inventory costs while yielding a desired level of aggregate factory production.