Theoretical Development based Nature-Inspired Optimization Algorithms: Applications and Challenges
Prerna Sharma, Kapil Sharma · 2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) · 2022
The process to achieve optimal solutions is becoming complex as the data generation is being proliferated. The intelligent metaheuristics algorithms are being recognized to obtain the optimal solution for these complex optimization problems, especially when there are various constraints to solve these problems. Many novel algorithms are being developed to find efficient approaches for handling these optimization problems. These algorithms are either exploring their application in a different context or are being enhanced to handle problems in different areas efficiently. There is rapid development in this field which results in unawareness regarding their application in different domains. This paper identifies the popular nature-inspired optimization algorithms by discussing their developments, principles and domain of application to address the gap of unawareness. Specifically, we have analyzed and explored the subsequent algorithms grasshopper, binary bat, chicken swarm, and cuttlefish algorithm. This review can also act as a guide to choose appropriate algorithms for future studies. Owing to the absence of significant literature, we have identified various nature-inspired algorithms having tremendous scope in theory and application.