This paper proposes a novel metaheuristic Child Drawing Development Optimization (CDDO) algorithm inspired by the child's learning behaviour and cognitive development using the golden ratio to optimize the beauty behind their art. The golden ratio was first introduced by the famous mathematician Fibonacci. The ratio of two consecutive numbers in the Fibonacci sequence is similar, and it is called the golden ratio, which is prevalent in nature, art, architecture, and design. CDDO uses golden ratio and mimics cognitive learning and child's drawing development stages starting from the scribbling stage to the advanced pattern-based stage. Hand pressure width, length and golden ratio of the child's drawing are tuned to attain better results. This helps children with evolving, improving their intelligence and collectively achieving shared goals. CDDO shows superior performance in finding the global optimum solution for the optimization problems tested by 19 benchmark functions. Its results are evaluated against more than one state of art algorithms such as PSO, DE, WOA, GSA, and FEP. The performance of the CDDO is assessed, and the test result shows that CDDO is relatively competitive through scoring 2.8 ranks. This displays that the CDDO is outstandingly robust in exploring a new solution. Also, it reveals the competency of the algorithm to evade local minima as it covers promising regions extensively within the design space and exploits the best solution.

中文翻译：

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基于儿童认知发展的儿童绘画发展优化算法

本文受儿童的学习行为和认知发展的启发，提出了一种新颖的元启发式儿童绘画发展优化 (CDDO) 算法，使用黄金比例来优化他们艺术背后的美感。黄金比例最早是由著名数学家斐波那契提出的。斐波那契数列中两个连续数字的比例相似，称为黄金比例，普遍存在于自然、艺术、建筑和设计中。CDDO 使用黄金比例，模拟从涂鸦阶段到高级模式阶段的认知学习和儿童绘画发展阶段。调整儿童画的手压宽度、长度和黄金比例，以达到更好的效果。这有助于孩子不断发展，提高他们的智力并共同实现共同的目标。CDDO 在为 19 个基准函数测试的优化问题寻找全局最优解方面表现出卓越的性能。它的结果是根据一种以上的最先进算法（例如 PSO、DE、WOA、GSA 和 FEP）进行评估的。对CDDO的性能进行评估，测试结果显示CDDO通过2.8个等级的评分具有相对的竞争力。这表明 CDDO 在探索新解决方案方面非常稳健。此外，它还揭示了算法逃避局部最小值的能力，因为它广泛地覆盖了设计空间内的有希望的区域并利用了最佳解决方案。它的结果是根据一种以上的最先进算法（例如 PSO、DE、WOA、GSA 和 FEP）进行评估的。对CDDO的性能进行评估，测试结果显示CDDO通过2.8个等级的评分具有相对的竞争力。这表明 CDDO 在探索新解决方案方面非常稳健。此外，它还揭示了算法逃避局部最小值的能力，因为它广泛地覆盖了设计空间内的有希望的区域并利用了最佳解决方案。它的结果是根据一种以上的最先进算法（例如 PSO、DE、WOA、GSA 和 FEP）进行评估的。对CDDO的性能进行评估，测试结果显示CDDO通过2.8个等级的评分具有相对的竞争力。这表明 CDDO 在探索新解决方案方面非常稳健。此外，它还揭示了算法逃避局部最小值的能力，因为它广泛地覆盖了设计空间内的有希望的区域并利用了最佳解决方案。