Abstract

This paper proposes a novel metaheuristic Child Drawing Development Optimization (CDDO) algorithm inspired by the child's learning behavior 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.

Highlights

  • Metaheuristic algorithms have been being used to solve today's real-world optimization problems, which can not be solved by traditional mathematical techniques [1]

  • 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 results obtained by the CDDO are shown, and it is compared with the results of the following algorithms Whale Optimization Algorithm (WOA), Differential Evolution (DE), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Fast Evolutionary Programming (FEP), published [35], [36]

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Summary

Introduction

Metaheuristic algorithms have been being used to solve today's real-world optimization problems, which can not be solved by traditional mathematical techniques [1] They are defined as higher-level strategies guiding the heuristic procedures that are more problem-specific to increase their performance [2]. The contribution of this study is the novelty of the notion behind the suggested algorithm that implements the method of child’s cognitive development and child’s drawing development stages backed up by its solid mathematical base using the golden ratio. Both techniques have never been used before in any metaheuristic researches, neither in computer science nor in nature-inspired algorithms.

Literature Review
Drawing Development Stages
First stage
Second stage
Third stage
Fourth stage
CDDO Stages A detailed description of each stage is explained as follows
Algorithm flow and pseudo code of CDDO
Benchmark Functions
Numerical Experiments
Results and Evaluations
Conclusion
Full Text
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