A Unique Metaheuristic Algorithm for Human Urbanisation

In the past ten years, there has been a rise in the popularity of metaheuristic algorithms, which make use of heuristic methods in order to find optimal solutions. Additionally, many distinct algorithms that are inspired by nature have been developed in order to improve the quality of solutions and the rate at which they converge. The author of this piece suggests a novel metaheuristic search for optimization that is based on human behaviour, with the intention of easing the transition to urban living and improving people's overall quality of life. In order to locate the intended outcome, this algorithm makes use of a wide range of search strategies, including population management and agent concentration, open and limited scope combination searching, and many more. The suggested method outperforms more strong algorithms already in use in the majority of search domains, as shown by the results of a number of different assessments using a range of different test functions.