Effects of Learning on Optimal Lot Size
Abstract
This paper deals with the effects of learning on the calculation of optimal economic lot sizes in intermittent production.
It is assumed that the manufacturing time of the lots is of such length that phenomena usually called “learning” can be encountered within each lot. The three different cases that can occur are incorporated into a model which demonstrates that the traditional lot size formulae may well indicate lots that are smaller than the true optimum. Numerical examples show the significance of these differences.
A simple deterministic model is used but results are seen to be extended easily to more complex cases.

