Genetic algorithm for multi-level assembly systems under stochastic lead times

The aim of this paper is to propose models to adapt and parameterize the Material Requirement Planning (MRP) approach under lead time uncertainty. Multi-level assembly systems with one type of finished products and several types of components aer studied. Each component has a fixed unit inventory cost and the finished product has a backlogging cost per unit of time. The lead times of components are discrete random variables, and the costumer’s demand of the finished product is known. A general mathematical model for supply planning of multi-level assembly systems is presented. A Genetic Algorithm (GA) method is proposed to minimize the sum of the average inventory holding cost for components and the average backlogging and inventory holding costs for the finished product.