Enhancing Pressure Vessel Design Optimization with a Hybrid CSA-PSO Algorithm

Ammar  Adel Ahmed; Amera Istiqlal Badran; Ibrahim M. Ahmed; Yahya T. Qassim; Dilovan Asaad Zebari; Reving Masoud Abdulhakeem

Authors

Ammar Adel Ahmed Department of Computer Science, College of Education for Pure Sciences, University of Mosul
Amera Istiqlal Badran Department of Computer Sciences, College of Computer Sciences and Mathematics, University of Mosul
Ibrahim M. Ahmed Department of Cybersecurity, College of Computer Science and Mathematics, University of Mosul
Yahya T. Qassim School of Engineering and Built Environment- Electrical and Electronic Engineering, Griffith University
Dilovan Asaad Zebari Department of Information Technology, Technical College of Informatics, Akre University for Applied Sciences
Reving Masoud Abdulhakeem Computer and Communication Engineering Department, Nawroz University

Keywords:

Metaheuristics Algorithms, Constrained Problem, Welded Beam Design problem, Big Bang–Big Crunch, Cuckoo Search Algorithm, Artificial Bee Colony, Vibrating Particles System, Water Evaporation Optimization.

Abstract

The optimization of the Pressure Vessel Design Problem (PVDP) plays a crucial role in various engineering applications where structures with the most efficient material utilization are required. However, the intricate interplay between design parameters and strict constraints presents a significant barrier for classical optimization algorithms to efficiently traverse the convoluted landscape of PVDP. Applying metaheuristic algorithms has been introduced as a solution to tackle these problems. The techniques introduced have the potential to confront the difficulties associated with nonlinearity, multimodality, and complex constraints that are frequently encountered in complex engineering optimization problems. This work carries out a comprehensive and comparative analysis of the performance of well-established metaheuristic algorithms in solving the PVDP. The methods under consideration at present are Big Bang –Big Crunch (BB-BC), Cuckoo Search Algorithm (CSA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Vibrating Particles System (VPS), and Water Evaporation Optimization (WEO). Third, we introduced the CSA-PSO algorithm. Through extensive numerical experiments, their rates of convergence, the quality of the solutions, and the amount of computation required are compared and analyzed, revealing their relative pros and cons in terms of the PVDP. As a result, the knowledge of how metaheuristic algorithms perform on the PVDP can be exploited when selecting optimization methods.