## 4 Simulation Models and Sustainability: Characterization
### Agent-Based Simulation  
Agent-based Simulation/Modeling (ABS/M) or Individual-based modeling (IBM) has been developed as a solution to the need for modeling natural systems [103]. It finds its conceptual beginnings with the examination of complex systems, adaptive systems, and modeling of biological systems. The ABS constructs a conceptual model through a  
Figure 11: The figure shows the network of keywords used in the collected papers where DES is utilized in sustainability assessment in the case of manufacturing and SC. The network shows a pre-eminence in energy consumption and management. Bottleneck reduction and assembly cell also find a dominant place in research pointing to DES being predominantly used at the operational level. bottom-up approach, by taking into account discrete entities or agents with an assumed behavior which is then simulated using software [104]. \"Agent\" is a representation of a component that is present in a \"social\" setting and that may or may not be construed as being intelligent [105]. The agents are presumed to be both individuals as well as collections (such as groups, networks, etc.). A benefit of using agents in the case of simulation is that they address both autonomy and complexity as they are distributed, adaptive to changes, and exhibit intelligence. They may also show learning behavior and rationality while using simple decision-making rules [106]. The characteristics of the agents are described as:  
* Agent is located in a dynamic environment and behaves autonomously and intelligently in that environment;
* The environment of the agents can have other agents and the system, as a consequence, is known as multi-agent system. Consequently, the agent-based models are composed of the following:
* Various agents with specified agent granularity;
* Rules for making decisions;
* Learning rules whereby the agents modify their behavior based on past outcomes;
* Social interaction of the agents;
* The environment. As described below, Figure 12 depicts the structure of a typical agent-based model. Some of the advantages of using agent-based models cited in the literature include [107]:  
* Agents are individually modeled and consequently monitored which makes determining the state of the agent at a particular time easy;
* Possibility of modeling large-scale complex systems which are also termed massively multi-agent systems (MMAS);
* ABS while capturing the emergent phenomena. The emergent phenomena may have characteristics different from that of the constituents of the system that ABS is able to capture. Many agent-based models exhibit the trait of emergence, which happens when some attribute that may be expressed at the system level is not expressly encoded at the individual level;
* ABS provides a natural description of the system while retaining flexibility. The property of natural description in ABS is linked to the presence of behavioral characteristics of the agents. Whereas flexibility refers to the possibility of adding or subtracting the agents from the model when needed. The application of the ABS has benefits over other simulation techniques. However, owing to high costs and complexity, these benefits are not absolute. The ABM is computationally intensive as simulation a large number of agents requires huge computational  
Figure 12: The figure describes how an ABM is built from the bottom. The autonomous and interactive nature of the agents renders complex modeling possible. The agents in addition to interacting with other agents can also interact with the real-world actors as well. power. ABM also requires that the modeler should have data regarding the elements of the model, as without any knowledge or an educated opinion of the operation of the system, it is not possible to build the model. In recent times, the use of ABS has been at the forefront in research and has been applied more than DES and SD. Appendix A.2 indicates the recent representative research wherein ABS has been used in modeling sustainability in manufacturing and allied SCs.