An Improved Archimedes Optimization Algorithm for Solving Optimization Problems

The Archimedes Optimization Algorithm (AOA) algorithm, a multi-agent-based metaheuristic, has garnered attention for its remarkable accuracy in real-world optimization. This research addresses solutions for the inherent limitation of original AOA, notably its susceptibility to uneven exploration and...

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Vydané v:2023 IEEE 8th International Conference on Recent Advances and Innovations in Engineering (ICRAIE) s. 1 - 5
Hlavní autori: Ahmad, Mohd Ashraf, Islam, Muhammad Shafiqul, Rashid, Muhammad Ikram Mohd
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Jazyk:English
Vydavateľské údaje: IEEE 02.12.2023
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Abstract The Archimedes Optimization Algorithm (AOA) algorithm, a multi-agent-based metaheuristic, has garnered attention for its remarkable accuracy in real-world optimization. This research addresses solutions for the inherent limitation of original AOA, notably its susceptibility to uneven exploration and exploitation phases and its propensity to become ensnared in local optima. To overcome these limitations, we employ two strategies: the modification of the density decreasing factor and the introduction of a safe updating mechanism inspired by game theory. These enhancements are subjected to rigorous evaluation using 23 benchmark functions, and their performance is compared against that of the original AOA and other prominent algorithms, including the Multiverse Optimization (MVO), Grasshopper Optimization Algorithm (GOA), Sine Cosine Algorithm (SCA), and Ant Lion Optimizer (ALO). The test results reveal significant improvements achieved by the newly proposed improved AOA (IAOA), surpassing the performance of the original AOA in 69% of the optimization cases among the 23 test functions. It is noteworthy that it also outperformed the other mentioned algorithms. The potential of the proposed algorithm as an effective tool for addressing real-world optimization challenges is underscored by these encouraging findings, adhering to research conventions.
AbstractList The Archimedes Optimization Algorithm (AOA) algorithm, a multi-agent-based metaheuristic, has garnered attention for its remarkable accuracy in real-world optimization. This research addresses solutions for the inherent limitation of original AOA, notably its susceptibility to uneven exploration and exploitation phases and its propensity to become ensnared in local optima. To overcome these limitations, we employ two strategies: the modification of the density decreasing factor and the introduction of a safe updating mechanism inspired by game theory. These enhancements are subjected to rigorous evaluation using 23 benchmark functions, and their performance is compared against that of the original AOA and other prominent algorithms, including the Multiverse Optimization (MVO), Grasshopper Optimization Algorithm (GOA), Sine Cosine Algorithm (SCA), and Ant Lion Optimizer (ALO). The test results reveal significant improvements achieved by the newly proposed improved AOA (IAOA), surpassing the performance of the original AOA in 69% of the optimization cases among the 23 test functions. It is noteworthy that it also outperformed the other mentioned algorithms. The potential of the proposed algorithm as an effective tool for addressing real-world optimization challenges is underscored by these encouraging findings, adhering to research conventions.
Author Islam, Muhammad Shafiqul
Rashid, Muhammad Ikram Mohd
Ahmad, Mohd Ashraf
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  fullname: Ahmad, Mohd Ashraf
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  givenname: Muhammad Shafiqul
  surname: Islam
  fullname: Islam, Muhammad Shafiqul
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  organization: University Malaysia Pahang Al-Sultan Abdullah,Faculty of Electrical and Electronics Engineering,Pekan,Malaysia
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  givenname: Muhammad Ikram Mohd
  surname: Rashid
  fullname: Rashid, Muhammad Ikram Mohd
  email: mikram@ump.edu.my
  organization: University Malaysia Pahang Al-Sultan Abdullah,Faculty of Electrical and Electronics Engineering,Pekan,Malaysia
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Snippet The Archimedes Optimization Algorithm (AOA) algorithm, a multi-agent-based metaheuristic, has garnered attention for its remarkable accuracy in real-world...
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SubjectTerms Archimedes Optimization Algorithm (AOA)
Benchmark testing
Game theory
Games
Heuristic algorithms
Improved Archimedes Optimization Algorithm (IAOA)
Meta-heuristic Algorithm
Metaheuristics
Optimization
Safe Experimentation Dynamics Algorithm (SED)
Technological innovation
Title An Improved Archimedes Optimization Algorithm for Solving Optimization Problems
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