In the literature review, we first explain the modeling process before discussing the different simulation and modeling methods and interpreting the modeling methods to the company scale.I. Modeling Process: The powerful technique that allows researchers from diverse backgrounds to analyze and study complex phenomena is modeling. In general, the model is “a (small) finite description of an infinitely complex reality, constructed with the aim of answering particular questions” (Kuipers 1994). Although in each scientific discipline the steps followed in the modeling process differ, the following general modeling method is as follows: Step 1: Model Identification – this step aims to identify the objectives of the study and the best method to model a particular event. This step also involves defining model boundaries that identify key variables and requirements for the scope, timeline, and way of referencing the model. Step 2: Model Building – aims to represent the real-world influences between the variables of interest in an appropriate layout. . This can be applied using a quantitative approach such as defining a system of simultaneous ordinary differential equations (ODEs) or linear programming or a qualitative approach such as a structural dependence representation using cause and effect diagrams. There are other hybrid methods that can be adopted, which combine quantitative and qualitative techniques. Step 3: Model analysis and interpretation – which gives the derivation of results for mathematical equations and/or simulation of relationships between variables, which in turn gives the solution for the particular research questions or criteria that have been defined at the start of the process. This may require additional steps such as the model...... middle of document...... because the variables in the model are not explicitly defined and therefore may not be easy to analyze.3. Other hybrid approaches: Various hybrid approaches are the macroeconomic model (IMEM) of Chen and Sun (2000) which combines quantitative and qualitative reasoning methods to model the economy, fuzzy cognitive maps (a combination of fuzzy logic and neural networks ) by Stylios and Groumpos (1998) which explains the method of modeling a two-level manufacturing control system and the explanation of the application of mixed qualitative and quantitative modeling approaches merging principal component analysis, as well as grouped fuzzy diagrams and reasoning for modeling a continuous stirred tank reactor and distillation column from Yadegar and Pishvaie (2005). A utility cost function, which can be used to estimate the accuracy of alternative modeling techniques, is also suggested..