This paper aims to demonstrate a simulation-optimization modeling approach to examine the efficiency of a mathematical model in Optimization of Multi-Commodities Consumer Supply Chain (MCCSC) — Modeling. Simulation is one of the most widely used tools in model validation. It enables identifying system's behaviors under different circumstances. To this end, in the present work, a supply chain system simulation model is developed within the context of production-distribution (P-D) decision making. Also, taking into account real-life constraints, an integrated MCCSC case study is created to predict the consequences of variable changes. The performance of the model is then evaluated using SimEvents toolbox in conjunction with Simulink toolbox of MALAB. Finally, Genetic Algorithmsare utilized to minimize the total cost of the entire system.