A simulation optimization approach-based genetic algorithm for lot sizing problem in a MTO sector

Abstract

In this paper, a combined simulation and Genetic Algorithm (GA) optimization model is developed to solve the Lot Sizing Problem (LSP) in a Make to Order (MTO) supply chain. The simulation model is performed using ARENA software. GA model is implemented using Visual Basic for Application (VBA) language, because it ensures exchanges between ARENA software and Ms Excel. The GA and simulation models operate in parallel over time with interactions. The case study's objective is to determine a fixed optimal lot size for each manufactured product type that will ensure order mean flow time target for each finished product. The comparative results with OptQuest software, which is used a global search method, to illustrate the efficiency and effectiveness of the proposed approach.