Discussing the article: "Arithmetic Optimization Algorithm (AOA): From AOA to SOA (Simple Optimization Algorithm)"
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Check out the new article: Arithmetic Optimization Algorithm (AOA): From AOA to SOA (Simple Optimization Algorithm).
The Arithmetic Optimization Algorithm (AOA) is an original method based on simple arithmetic operations such as addition, subtraction, multiplication and division. Its essence lies in using these basic mathematical principles to find optimal solutions to a variety of problems. AOA was developed by a team of researchers including Laith Abualigah and first introduced in 2021. The algorithm belongs to the class of metaheuristic methods (high-level algorithms) aimed at finding, generating and probabilistically choosing from several heuristics that can provide high-quality solutions in a reasonable time for complex optimization problems where accuracy-based methods may be ineffective or impossible.
This method caught my attention because of its simple and, at the same time, elegant idea of using completely elementary arithmetic operators. The relationship between these basic mathematical operations and metaheuristic approaches creates a synergy that allows solving complex optimization problems. The metaheuristic methods used in AOA include several key principles:
1. Population approach. AOA uses a population of solutions, which allows it to cover a wider space of possible solutions. This helps to avoid local optima and expands the search horizons.
2. Randomness and stochasticity. Incorporating elements of randomness into the search helps algorithms avoid getting stuck in local optima and provides a more complete exploration of the solution space, which increases the probability of finding a global optimum.
3. Balance between exploration and exploitation. Like many other metaheuristic algorithms, AOA strives for a balance between exploring new regions of the solution space and exploiting already known efficient solutions. This is achieved by using arithmetic operations to update the positions of solutions.
Author: Andrey Dik