Over the last few decades, there have been numerous metaheuristic optimization algorithms developed with varying inspiration sources. However, most of these metaheuristics have one or more weaknesses that affect their performances, for example:
Metaheuristics are frequently improved by adding efficient mechanisms aimed at increasing their performance like opposition-based learning, chaotic function, etc. What are the best efficient mechanisms you suggest?
To address the problem that metaheuristic algorithms easily fall into local optimum, the article "Improved Harris hawks optimization for non-convex function optimization and design optimization problems" (DOI: 10.1016/ j.matcom.2022.09.010) proposed a novel mutation strategy based on Brownian motion, and the experimental results show that the strategy can effectively help the algorithm jump out of the local optimum
In this article standard deviation is presented as a tool to balance exploration and exploitation for a mutation operation that brings diversity in the population. Similar type of strategy may be tested for different meta-heuristics and problems.
https://www.researchgate.net/publication/353040925_Balancer_Genetic_Algorithm-A_Novel_Task_Scheduling_Optimization_Approach_in_Cloud_Computing?_sg%5B0%5D=Ui3QEAZN-zvjDCVFnsrfKkxqWyOxnJJL8o2ieDPQTId69nzjm7W00drXmn5KIspPx6VLAZVfBqCVSridq-BxnqBPepIl0lUlsE-HP-lD.DwLNgn9rV9HoqIbOI2OauxDKV-jlmiNBgBR7XUKOn_WytoXWbzfjfPQC7ztohIANh9oxe1_4vw_fV9Xhm-6d1A
Fact: A metaheuristic neighborhood search that is trapped in a local optimum for a rugged-elementary landscape can be modified to a 2-step neighborhood search (by using the squared neighborhood adjacency matrix). Next paper shows that this leads to a favorable smooth-elementary landscape: Applied Mathematics Letters, Volume 16, Issue 3, April 2003, Pages 337-343.
Providing a proper balance between exploration and exploitation is a good choice.
Article Metaheuristic Algorithms in Optimal Power Flow Analysis: A Q...
In this article a highly complex optimization problem such as optimal power flow is computed through various metaheuristics with varied performance.
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