Artificial Soul Optimization - An Invention
DOI:
https://doi.org/10.14738/tmlai.75.7322Keywords:
Artificial Souls, Artificial Soul Optimization, Artificial Soul Computing, Computational Intelligence, Evolutionary Computing, Particle Swarm Optimization, Genetic Algorithms, Artificial Human Optimization, Bio-Inspired Computing, Nature Inspired Computing, Machine Learning, Artificial IntelligenceAbstract
The Soul is eternal and exists even after death of a person or animal. The main idea that is captured in this work is that soul continues to exist and takes a different a body after the death. The primary goal of this work is to invent a new field titled "Artificial Soul Optimization (ASO)". The term "Artificial Soul Optimization" is coined in this paper. All the Optimization algorithms which are proposed based on Artificial Souls will come under "Artificial Soul Optimization" Field (ASO Field). In the Particle Swarm Optimization and Artificial Human Optimization, the basic entities in search space are Artificial Birds and Artificial Humans respectively. Similarly, in Artificial Soul Optimization, the basic entities in search space are Artificial Souls. In this work, the ASO Field concepts are added to Particle Swarm Optimization (PSO) algorithm to create a new hybrid algorithm titled "Soul Particle Swarm Optimization (SoPSO). The proposed SoPSO algorithm is applied on various benchmark functions. Results obtained are compared with PSO algorithm. The World's first Hybrid PSO algorithm based on Artificial Souls is created in this work.
References
(1) Veda Vyasa, Srimad Bhagavatha Purana. Ancient Hindu Religious Text.
(2) Veda Vyasa, Bhagavad Gita. Ancient Hindu Religiuos Text.
(3) Saptarshi Sengupta, Sanchita Basak, Richard Alan Peters II. Particle Swarm Optimization: A survey of historical and recent developments with hybridization perspectives. https://arxiv.org/abs/1804.05319, 2018.
(4) Yudong Zhang, Shuihua Wang, and Genlin Ji, “A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications,” Mathematical Problems in Engineering, vol. 2015, Article ID 931256, 38 pages, 2015. https://doi.org/10.1155/2015/931256.
(5) M. R. AlRashidi, M. E. El-Hawary. A Survey of Particle Swarm Optimization Applications in Electric Power Systems. IEEE Transactions on Evolutionary Computation. Volume 13, Issue 4, August 2009.
(6) Sharandeep Singh. A Review on Particle Swarm Optimization Algorithm. International Journal of Scientific & Engineering Research, Volume 5, Issue 4, April-2014.
(7) T. Saravanan and V. Srinivasan. Overview of Particle Swarm Optimization. Indian Journal of Science and Technology, Vol 8(32), November 2015.
(8) Muhammad Imran, Rathiah Hashim, Noor Elaiza Abd Khalid.An Overview of Particle Swarm Optimization Variants. Procedia Engineering. Elsevier.Volume 53, Pages 491-496, 2013.
(9) Riccardo Poli, James Kennedy, Tim Blackwell. Particle swarm optimization - An overview. Swarm Intelligence. Volume 1, Issue 1, pp 33–57, Springer, 2007.
(10) Liu H, Xu G, Ding GY, Sun YB, “Human behavior-based particle swarm optimization”, The Scientific World Journal, 2014.
(11) Ruo-Li Tang, Yan-Jun Fang, "Modification of particle swarm optimization with human simulated property", Neurocomputing, Volume 153, Pages 319–331, 2015.
(12) Muhammad Rizwan Tanweer, Suresh Sundaram, "Human cognition inspired particle swarm optimization algorithm", 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2014.
(13) M.R. Tanweer, S. Suresh, N. Sundararajan, "Self regulating particle swarm optimization algorithm", Information Sciences: an International Journal, Volume 294, Issue C, Pages 182-202, 2015.
(14) M. R. Tanweer, S. Suresh, N. Sundararajan, "Improved SRPSO algorithm for solving CEC 2015 computationally expensive numerical optimization problems", 2015 IEEE Congress on Evolutionary Computation (CEC), pp. 1943-1949, 2015.
(15) Satish Gajawada. “POSTDOC : The Human Optimization”, Computer Science & Information Technology (CS & IT), CSCP, pp. 183-187, 2013.
(16) Satish Gajawada. “CEO: Different Reviews on PhD in Artificial Intelligence”, Global Journal of Advanced Research, vol. 1, no.2, pp. 155-158, 2014.
(17) Satish Gajawada. “Entrepreneur: Artificial Human Optimization”. Transactions on Machine Learning and Artificial Intelligence, Volume 4 No 6 December (2016); pp: 64-70
(18) Satish Gajawada. “Artificial Human Optimization – An Introduction”, Transactions on Machine Learning and Artificial Intelligence, Volume 6, No 2, pp: 1-9, April 2018
(19) Satish Gajawada. “An Ocean of Opportunities in Artificial Human Optimization Field”, Transactions on Machine Learning and Artificial Intelligence, Volume 6, No 3, June 2018
(20) Satish Gajawada. “25 Reviews on Artificial Human Optimization Field for the First Time in Research Industry”, International Journal of Research Publications, Vol. 5, no. 2, United Kingdom.
(21) Satish Gajawada and Hassan M. H. Mustafa, “Collection of Abstracts in Artificial Human Optimization Field”, International Journal of Research Publications, Volume 7, No 1, United Kingdom, 2018.
(22) Satish Gajawada, Hassan M. H. Mustafa, HIDE : Human Inspired Differential Evolution - An Algorithm under Artificial Human Optimization Field , International Journal of Research Publications (Volume: 7, Issue: 1), http://ijrp.org/paper-detail/264
(23) Satish Gajawada, Hassan M. H. Mustafa , Artificial Human Optimization – An Overview. Transactions on Machine Learning and Artificial Intelligence, Volume 6, No 4, August 2018.
(24) Satish Gajawada, Hassan M. H. Mustafa, Testing Multiple Strategy Human Optimization based Artificial Human Optimization Algorithms, Computer Reviews Journal, vol. 1, no.2, 2018.
(25) Satish Gajawada, Hassan M. H. Mustafa. Hybridization Concepts of Artificial Human Optimization Field Algorithms Incorporated into Particle Swarm Optimization. International Journal of Computer Applications 181(19):10-14, September 2018.
(26) Satish Gajawada, Hassan M. H. Mustafa (2018). An Artificial Human Optimization Algorithm Titled Human Thinking Particle Swarm Optimization. International Journal of Mathematical Research, 7(1): 18-25. DOI: 10.18488/journal.24.2018.71.18.25
(27) Satish Gajawada, Hassan Mustafa: Novel Artificial Human Optimization Field Algorithms - The Beginning. CoRR abs/1903.12011(2019)
(28) Satish Gajawada, Hassan M. H. Mustafa: Ten Artificial Human Optimization Algorithms. Transactions on Machine Learning and Artificial Intelligence, Volume 7, No 3, June 2019.