Simulation Based Optimization of Lot Sizes for Opposing Logistic Objectives

Abstract

The objective of this study is to optimize the lot sizes for three different products based on storage cost, set up cost and logistic key performance indicators (KPIs) such as delivery reliability. Two methods including a mathematical model and the static method of Andler’s lot size were originally used to solve this problem. However, both methods produce lot sizes that underperform according to logistic KPIs. For that reason, a simulation considering dynamic behavior and logistic performance is developed to heuristically optimize the lot sizes while being restricted to a minimum standard of delivery reliability. The study indicates that modifying the lot sizes will improve the logistic performance without increasing the total costs drastically. Compared to Andler’s static method, the heuristically-optimized lot sizes show an average increase of the delivery reliability by 7% and a reduction of the total cost by 13%. Throughput time was raised by more than 25% and the utilization elevated by 4%.