Abstract In the recent decade, the application of metaheuristic algorithms for optimization and solving different problems is increased and various nature-inspired algorithms are designed to improve the quality and convergence speed of getting the answer. In this essay, a novel metaheuristic search for optimization inspired by human behavior for urbanization and improving life situations is proposed. This algorithm uses different strategies including combined searching in an open and limited scope and population management and concentration of agents in the search process. The evaluation results using a wide range of different test functions show the prevalence of the proposed algorithm compared with other potent algorithms in most search spaces.

中文翻译：

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人类城市化算法：一种新颖的元启发式方法

摘要 近十年来，元启发式算法在优化和解决不同问题中的应用越来越多，并设计了各种受自然启发的算法来提高得到答案的质量和收敛速度。在本文中，提出了一种受人类行为启发的新型元启发式优化搜索，以实现城市化和改善生活状况。该算法使用不同的策略，包括在开放和有限范围内的组合搜索以及搜索过程中的人口管理和代理集中。使用各种不同测试函数的评估结果表明，与大多数搜索空间中的其他有效算法相比，所提出的算法的普遍性。