Minimising total cost with regular and emergency outsourcing sources: a neuro-dynamic programming approach

Abstract

This study models and explains the business situation of an organisation which has regular and emergency outsourcing sources and where decisions have to be made at the beginning of every period regarding how much to order from these sources, so as to balance between different cost components of current and future periods. Previous works in this area have tried to attack this problem with dynamic programming. In this project, neuro-dynamic programming has been applied, and the reasons for doing so have been clearly stated. This model not only derives policies in order to minimise the expected total discounted cost over a period of time, but also enables the system to learn to make such decisions, and to improve its actions by using reinforcement learning. The performance of the present work has been measured quantitatively and has been compared with the models stated in literature. This study will be very useful for the organisations where such business problems exist or are likely to exist. This study will also be of great use to researchers, who are keen to understand and model the given business situation with distribution independent demand based models.