Child Drawing Development Optimization Algorithm Based on Child's Cognitive Development

被引:48
作者
Abdulhameed, Sabat [1 ]
Rashid, Tarik A. [1 ]
机构
[1] Univ Kurdistan Hewler, Comp Sci & Engn Dept, Erbil, Krg, Iraq
关键词
Nature-inspired algorithm; Metaheuristic algorithms; Optimization algorithms; Golden ratio; Mathematical models; Child drawing development optimization; CDDO;
D O I
10.1007/s13369-021-05928-6
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:1337 / 1351
页数:15
相关论文
共 36 条
[1]   Fitness Dependent Optimizer: Inspired by the Bee Swarming Reproductive Process [J].
Abdullah, Jaza Mahmood ;
Rashid, Tarik Ahmed .
IEEE ACCESS, 2019, 7 :43473-43486
[2]  
Abraham Ajith., 2008, Soft Comput. Knowl. Discov Data Min., P279, DOI [10.1007/978-0-387-69935-6_12, DOI 10.1007/978-0-387-69935-6_12]
[3]  
Abualigah L.M. Q., 2019, Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering, V816, DOI DOI 10.1007/978-3-030-10674-4
[4]   Aquila Optimizer: A novel meta-heuristic optimization algorithm [J].
Abualigah, Laith ;
Yousri, Dalia ;
Abd Elaziz, Mohamed ;
Ewees, Ahmed A. ;
Al-qaness, Mohammed A. A. ;
Gandomi, Amir H. .
COMPUTERS & INDUSTRIAL ENGINEERING, 2021, 157 (157)
[5]   The Arithmetic Optimization Algorithm [J].
Abualigah, Laith ;
Diabat, Ali ;
Mirjalili, Seyedali ;
Elaziz, Mohamed Abd ;
Gandomi, Amir H. .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2021, 376
[6]   Advances in Sine Cosine Algorithm: A comprehensive survey [J].
Abualigah, Laith ;
Diabat, Ali .
ARTIFICIAL INTELLIGENCE REVIEW, 2021, 54 (04) :2567-2608
[7]   No Free Lunch Theorem: A Review [J].
Adam, Stavros P. ;
Alexandropoulos, Stamatios-Aggelos N. ;
Pardalos, Panos M. ;
Vrahatis, Michael N. .
APPROXIMATION AND OPTIMIZATION: ALGORITHMS, COMPLEXITY AND APPLICATIONS, 2019, 145 :57-82
[8]  
Agarwal P., 2014, International Journal of Computer Applications, V100, P14, DOI [DOI 10.5120/17593-8331, 10.5120/17593-8331]
[9]  
Akhtaruzzamna M., 2011, International Journal of Arts, V1, P1, DOI DOI 10.5923/J.ARTS.20110101.01
[10]  
Akseer T., 2012, The Alberta Journal of Educational Research, V58, P300