## 4 Simulation Models and Sustainability: Characterization  
This section shall provide an exhaustive overview of the simulation models in use in the context of sustainability in SC. Simulation models can be characterized along three fundamental aspects:  
* Assessing the temporal aspect of the processes;
* Taking into consideration the randomness of the processes;
* In view of the organization of the process data. If the factor of time is addressed in the simulation, it is called a dynamic simulation and if not, it is termed as a static simulation. Dynamic modeling emulates an existing or possibly feasible system state to analyze the dynamic relationship between model variables and, in the case of sustainability, it generally consists of resorting to the use of the systems approach [63]. Dynamic simulation can further be classified as continuous or discrete such that in discrete simulations, the changes do not occur continuously but at given times. In the continuous simulation, the changes are assumed to have occurred continuously. Discrete event simulation is further characterized as time-stepped simulations and event-driven simulations. In the former, time intervals are assumed to be equal whereas, in the latter, the events or changes in the system are marked rendering the time intervals as unequal. A number of studies have compared continuous simulation and discrete event simulation. Sustainable manufacturing processes have been modeled and compared using both discrete event and system dynamics simulation so as to ascertain aspects that are appropriate for each modeling approach [64]. On the other hand, based on randomness, the simulation may be described as being deterministic or stochastic. In a deterministic simulation, each simulation run gives the same result whereas it is not the same in the case of the stochastic simulations. A study comparing the sustainable production planning approaches using deterministic and the stochastic method may be cited. A decision framework is presented which may guide the managers to choose between the two [65]. Finally, with regards to data management, a  
Figure 8: A keyword network of the published reviews in the field. Besides showing the pre-eminence of the CE and lifecycle assessment, the keyword network also presents sustainability-related concepts that deal with the idea whole paradigm of manufacturing rather than just the actual process of manufacturing. simulation can be either a grid-based simulation or a mesh-free simulation. A grid-based simulation construes a manufacturing plan as discrete cells and the simulations are done such that the relationship between various cells is taken to account. A mesh-free simulation derives data while conceiving individual entities [66]. The literature deliberates upon the issue of model resolution. Multi-resolution modeling is presented in contrast to hierarchical modeling [67]. In the case of modeling sustainability in manufacturing and SCs, the idea of multi-resolution modeling is presented as fundamentally essential as simulating sustainability in any context includes dealing with different levels simultaneously. Multi-resolution modeling is defined as the approach whereby a complete model is approached or parts of the model with different resolutions are addressed. It is brought about in a way whereby long-term questions are solved with low resolution whereas short-term questions use higher resolution models. An improvisation on the concept of multi-resolution modeling is the idea of a sustainable cockpit [68]. Additionally, the model presents a continuous modeling technique all the while conceiving of the system in discrete terms. Another aspect of the simulation is what is termed model magnification. Model magnification has been alluded to in the literature along different time frames. Models have been defined as being strategic, tactical, and operational [69]. Strategic models refer to time frame form five to ten years.