The Arithmetic Optimization Algorithm
This work proposes a new meta-heuristic method called Arithmetic Optimization Algorithm (AOA) that utilizes the distribution behavior of the main arithmetic operators in mathematics including (Multiplication (M), Division (D), Subtraction (S), and Addition (A)). AOA is mathematically modeled and imp...
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| Veröffentlicht in: | Computer methods in applied mechanics and engineering 2021-04, Vol.376, p.113609, Article 113609 |
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| container_title | Computer methods in applied mechanics and engineering |
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| creator | Abualigah, Laith Diabat, Ali Mirjalili, Seyedali Abd Elaziz, Mohamed Gandomi, Amir H. |
| description | This work proposes a new meta-heuristic method called Arithmetic Optimization Algorithm (AOA) that utilizes the distribution behavior of the main arithmetic operators in mathematics including (Multiplication (M), Division (D), Subtraction (S), and Addition (A)). AOA is mathematically modeled and implemented to perform the optimization processes in a wide range of search spaces. The performance of AOA is checked on twenty-nine benchmark functions and several real-world engineering design problems to showcase its applicability. The analysis of performance, convergence behaviors, and the computational complexity of the proposed AOA have been evaluated by different scenarios. Experimental results show that the AOA provides very promising results in solving challenging optimization problems compared with eleven other well-known optimization algorithms. Source codes of AOA are publicly available at and . |
| doi_str_mv | 10.1016/j.cma.2020.113609 |
| format | Article |
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AOA is mathematically modeled and implemented to perform the optimization processes in a wide range of search spaces. The performance of AOA is checked on twenty-nine benchmark functions and several real-world engineering design problems to showcase its applicability. The analysis of performance, convergence behaviors, and the computational complexity of the proposed AOA have been evaluated by different scenarios. Experimental results show that the AOA provides very promising results in solving challenging optimization problems compared with eleven other well-known optimization algorithms. 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AOA is mathematically modeled and implemented to perform the optimization processes in a wide range of search spaces. The performance of AOA is checked on twenty-nine benchmark functions and several real-world engineering design problems to showcase its applicability. The analysis of performance, convergence behaviors, and the computational complexity of the proposed AOA have been evaluated by different scenarios. Experimental results show that the AOA provides very promising results in solving challenging optimization problems compared with eleven other well-known optimization algorithms. Source codes of AOA are publicly available at and .</description><subject>Algorithm</subject><subject>Algorithms</subject><subject>AOA</subject><subject>Arithmetic</subject><subject>Arithmetic Optimization Algorithm</subject><subject>Artificial Intelligence</subject><subject>Benchmark</subject><subject>Computational Intelligence</subject><subject>Design engineering</subject><subject>Genetic Algorithm</subject><subject>Grey Wolf Optimizer</subject><subject>Heuristic</subject><subject>Heuristic methods</subject><subject>Meta-heuristics</subject><subject>Multiplication</subject><subject>Operators (mathematics)</subject><subject>Optimization</subject><subject>Optimization algorithms</subject><subject>Particle Swarm Optimization</subject><subject>Subtraction</subject><subject>Whale Optimization Algorithm</subject><issn>0045-7825</issn><issn>1879-2138</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kE1PwzAMhiMEEmPwA7hNQhw74rT5qDhNiC9p0i7jHKWJy1Kt60gyJPj1ZJQzvtiW_b62HkKugc6Bgrjr5rY3c0ZZ7qEUtD4hE1CyLhiU6pRMKK14IRXj5-Qixo7mUMAm5Ha9wdki-LTpMXk7W-2T7_23SX7YzRbb9-F3dEnOWrONePWXp-Tt6XH98FIsV8-vD4tlYSsQqTCKOWi5dFy1rnYNs1hzZxshgKI0ZVnKqkLDuKwZa4SkgHWZaxSqUdiIckpuRt99GD4OGJPuhkPY5ZOacQqMK8gmUwLjlg1DjAFbvQ--N-FLA9VHGrrTmYY-0tAjjay5HzWY3__0GHS0HncWnQ9ok3aD_0f9Az6YZU8</recordid><startdate>20210401</startdate><enddate>20210401</enddate><creator>Abualigah, Laith</creator><creator>Diabat, Ali</creator><creator>Mirjalili, Seyedali</creator><creator>Abd Elaziz, Mohamed</creator><creator>Gandomi, Amir H.</creator><general>Elsevier B.V</general><general>Elsevier BV</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20210401</creationdate><title>The Arithmetic Optimization Algorithm</title><author>Abualigah, Laith ; 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| ispartof | Computer methods in applied mechanics and engineering, 2021-04, Vol.376, p.113609, Article 113609 |
| issn | 0045-7825 1879-2138 |
| language | eng |
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| source | ScienceDirect Journals (5 years ago - present) |
| subjects | Algorithm Algorithms AOA Arithmetic Arithmetic Optimization Algorithm Artificial Intelligence Benchmark Computational Intelligence Design engineering Genetic Algorithm Grey Wolf Optimizer Heuristic Heuristic methods Meta-heuristics Multiplication Operators (mathematics) Optimization Optimization algorithms Particle Swarm Optimization Subtraction Whale Optimization Algorithm |
| title | The Arithmetic Optimization Algorithm |
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