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The process of building a model or copy of a real-world system and assessing its behaviour under various scenarios is referred to as simulation. Simulation in population genetics is the process of simulating a population's genetic makeup and evolutionary history using mathematical models and computer algorithms. It is important in population genetics for a better understanding of the impact of various evolutionary and demographic scenarios on sequence variation and patterns, it allows investigators to better assess and design analytical methods in the study of disease-associated genetic factors. This is an important tool for studying population genetic diversity and how natural selection, genetic drift, mutation, migration, and other evolutionary forces have influenced the genetic makeup of the population. There are three fundamental frameworks for simulation: coalescent, forward, and resampling methods. Numerous simulators that fit under these frameworks can be compared in terms of their evolutionary and demographic scenarios, computing complexity, and particular applications. Population simulation is becoming increasingly important in evolutionary biology, enabling researchers to explore the effects of various genetic models on genetic diversity and DNA sequence patterns. [ABSTRACT FROM AUTHOR]