Propagation Search Algorithm: A Physics-Based Optimizer for Engineering Applications

被引:14
作者
Qais, Mohammed H. [1 ]
Hasanien, Hany M. [2 ]
Alghuwainem, Saad [3 ]
Loo, Ka Hong [4 ]
机构
[1] Ctr Adv Reliabil & Safety, Hong Kong, Peoples R China
[2] Ain Shams Univ, Fac Engn, Elect Power & Machines Dept, Cairo 11517, Egypt
[3] King Saud Univ, Coll Engn, Elect Engn Dept, Riyadh 11421, Saudi Arabia
[4] Hong Kong Polytech Univ, Dept Elect & Informat Engn, Hong Kong, Peoples R China
关键词
algorithms; engineering optimization; metaheuristics; propagation search algorithm;
D O I
10.3390/math11204224
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
For process control in engineering applications, the fewer the coding lines of optimization algorithms, the more applications there are. Therefore, this work develops a new straightforward metaheuristic optimization algorithm named the propagation search algorithm (PSA), stirred by the wave propagation of the voltage and current along long transmission lines. The mathematical models of the voltage and current are utilized in modeling the PSA, where the voltage and current are the search agents. The propagation constant of the transmission line is the control parameter for the exploitation and exploration of the PSA. After that, the robustness of the PSA is verified using 23 famous testing functions. The statistical tests, comprising mean, standard deviation, and p-values, for 20 independent optimization experiments are utilized to confirm the robustness of the PSA to find the best result and the significant difference between the outcomes of the PSA and those of the compared algorithms. Finally, the proposed PSA is applied to find the optimum design parameters of four engineering design problems, including a three-bar truss, compression spring, pressure vessel, and welded beam. The outcomes show that the PSA converges to the best solutions very quickly, which can be applied to those applications that require a fast response.
引用
收藏
页数:26
相关论文
共 47 条
  • [1] Mantis Search Algorithm: A novel bio-inspired algorithm for global optimization and engineering design problems
    Abdel-Basset, Mohamed
    Mohamed, Reda
    Zidan, Mahinda
    Jameel, Mohammed
    Abouhawwash, Mohamed
    [J]. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2023, 415
  • [2] Kepler optimization algorithm: A new metaheuristic algorithm inspired by Kepler?s laws of planetary motion
    Abdel-Basset, Mohamed
    Mohamed, Reda
    Azeem, Shaimaa A. Abdel
    Jameel, Mohammed
    Abouhawwash, Mohamed
    [J]. KNOWLEDGE-BASED SYSTEMS, 2023, 268
  • [3] Nutcracker optimizer: A novel nature-inspired metaheuristic algorithm for global optimization and engineering design problems
    Abdel-Basset, Mohamed
    Mohamed, Reda
    Jameel, Mohammed
    Abouhawwash, Mohamed
    [J]. KNOWLEDGE-BASED SYSTEMS, 2023, 262
  • [4] African vultures optimization algorithm: A new nature-inspired metaheuristic algorithm for global optimization problems
    Abdollahzadeh, Benyamin
    Gharehchopogh, Farhad Soleimanian
    Mirjalili, Seyedali
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2021, 158
  • [5] Electromagnetic field optimization: A physics-inspired metaheuristic optimization algorithm
    Abedinpourshotorban, Hosein
    Shamsuddin, Siti Mariyam
    Beheshti, Zahra
    Jawawi, Dayang N. A.
    [J]. SWARM AND EVOLUTIONARY COMPUTATION, 2016, 26 : 8 - 22
  • [6] Reptile Search Algorithm (RSA): A nature-inspired meta-heuristic optimizer
    Abualigah, Laith
    Abd Elaziz, Mohamed
    Sumari, Putra
    Geem, Zong Woo
    Gandomi, Amir H.
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2022, 191
  • [7] Aquila Optimizer: A novel meta-heuristic optimization algorithm
    Abualigah, Laith
    Yousri, Dalia
    Abd Elaziz, Mohamed
    Ewees, Ahmed A.
    Al-qaness, Mohammed A. A.
    Gandomi, Amir H.
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2021, 157 (157)
  • [8] AEFA: Artificial electric field algorithm for global optimization
    Anita
    Yadav, Anupam
    [J]. SWARM AND EVOLUTIONARY COMPUTATION, 2019, 48 : 93 - 108
  • [9] Atomic orbital search: A novel metaheuristic algorithm
    Azizi, Mahdi
    [J]. APPLIED MATHEMATICAL MODELLING, 2021, 93 : 657 - 683
  • [10] White Shark Optimizer: A novel bio-inspired meta-heuristic algorithm for global optimization problems
    Braik, Malik
    Hammouri, Abdelaziz
    Atwan, Jaffar
    Al-Betar, Mohammed Azmi A.
    Awadallah, Mohammed A.
    [J]. KNOWLEDGE-BASED SYSTEMS, 2022, 243