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Human urbanization algorithm: A novel metaheuristic approach

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  • Ghasemian, Hadi
  • Ghasemian, Fahimeh
  • Vahdat-Nejad, Hamed

Abstract

In the recent decade, the application of metaheuristic algorithms for optimization and solving different problems is increased and various nature-inspired algorithms are designed to improve the quality and convergence speed of getting the answer. In this essay, a novel metaheuristic search for optimization inspired by human behavior for urbanization and improving life situations is proposed. This algorithm uses different strategies including combined searching in an open and limited scope and population management and concentration of agents in the search process. The evaluation results using a wide range of different test functions show the prevalence of the proposed algorithm compared with other potent algorithms in most search spaces.

Suggested Citation

  • Ghasemian, Hadi & Ghasemian, Fahimeh & Vahdat-Nejad, Hamed, 2020. "Human urbanization algorithm: A novel metaheuristic approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 178(C), pages 1-15.
    • Handle: RePEc:eee:matcom:v:178:y:2020:i:c:p:1-15
    DOI: 10.1016/j.matcom.2020.05.023
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    1. Oecd, 2009. "Climate Change and Africa," OECD Journal: General Papers, OECD Publishing, vol. 2009(1), pages 5-35.
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    1. Xin Li & Wanying Liu & Jingyuan Qiao & Yanhao Li & Jia Hu, 2023. "An Enhanced Semi-Flexible Transit Service with Introducing Meeting Points," Networks and Spatial Economics, Springer, vol. 23(3), pages 487-527, September.
    2. Khizer Mehmood & Naveed Ishtiaq Chaudhary & Khalid Mehmood Cheema & Zeshan Aslam Khan & Muhammad Asif Zahoor Raja & Ahmad H. Milyani & Abdulellah Alsulami, 2023. "Design of Nonlinear Marine Predator Heuristics for Hammerstein Autoregressive Exogenous System Identification with Key-Term Separation," Mathematics, MDPI, vol. 11(11), pages 1-20, May.

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