Playground Algorithm as a New Meta-heuristic Optimization Algorithm

Kemal Altwlkany, S. Konjicija
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Abstract

This paper presents a new meta-heuristic algorithm called Playground algorithm. The Playground algorithm is designed to model social interaction amongst children, and the mechanisms and operators of the algorithm are inspired by the model of child interaction and engagement in games during a child's stay at the playground. In order to evaluate the performance of the algorithm, a series of tests were performed over a class of functions selected so that they possess properties such as: multimodality / unimodality, (non) separability, (non) differentiability, (non) convexity, existence of ridges and valleys and multidimensionality. During testing, the values of the algorithm parameters are varied, in order to determine their recommended values. The analysis was carried out with an overview of the effects of the algorithm parameters on the performance of the algorithm in the problem area, performance in the criterion domain, and the execution time.
操场算法作为一种新的元启发式优化算法
本文提出了一种新的元启发式算法——Playground算法。Playground算法旨在模拟儿童之间的社交互动,算法的机制和操作人员的灵感来自儿童在操场上的互动和参与游戏的模型。为了评估该算法的性能,对选定的一类函数进行了一系列测试,使它们具有诸如:多模态/单模态、(非)可分性、(非)可微性、(非)凸性、脊谷存在性和多维性等特性。在测试过程中,算法参数的值是变化的,以确定它们的推荐值。在进行分析时,概述了算法参数对算法在问题域中的性能、在标准域中的性能和执行时间的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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