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Developing an arrangement or structure as entirely excellent functional or effectively as feasible is called optimization. Strategies that optimize or reduce certain research variables are found using methods of optimization. A higher-level heuristic called a metaheuristic, for short, is used in optimizing to create a process that effectively solves issues like limited computing power and partial, incomplete data. Estimating techniques were offered as a novel method for resolving complicated and multidimensional situations. Heuristic and metaheuristic algorithms are two prominent subcategories of these. Metaheuristic approaches are utilized for a variety of challenging and intricate optimal problems, while heuristic techniques are employed for local traps and solving specific optimal issues. Exploring and profiting are both goals of metaheuristic. This approach initially uses exploration to find solutions before moving on to exploitation, which increases the precision of the exploration phase. The use of metaheuristics in continuous, discrete, and optimization has increased significantly. Intelligent beings and organisms in nature create these kinds of algorithms. Many of these metaheuristic algorithms have recently been presented, and one of them is known as “African Vulture Optimization Algorithm (AVOA).” This suggested a lifestyle modeled by African vultures. Based to the fundamental ideas regarding vultures, the AVOA method is going to be developed in a step-by-step manner, with every requirement met and points defined in each stage. There are four phases in the AVOA technique: phases 1, 2, 3, and 4. Phase 1 is used to identify the best vultures for each group, Phase 2 is used to determine the pace at which vultures starve, Phase 3 is used for exploration, and Phase 4 is used for exploitation. African vulture algorithm for optimization holds optimization employing these stages. Consequently, we anticipate that the “African vulture optimization algorithm” will produce greater outcomes than any other algorithm that has been presented so far.

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A Unique Algorithm About Global Enhancement Problems Present in African Vulture Optimization Algorithm

  • 会议论文

  • 发表日期：

    2025年

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  • Suraya Mubeen,
  • Ganapathi Antharam,
  • B. Kavitha Rani,
  • Abdul Subhani Shaik,
  • P. Raveendra Babu,
  • Venkataiah

摘要

Developing an arrangement or structure as entirely excellent functional or effectively as feasible is called optimization. Strategies that optimize or reduce certain research variables are found using methods of optimization. A higher-level heuristic called a metaheuristic, for short, is used in optimizing to create a process that effectively solves issues like limited computing power and partial, incomplete data. Estimating techniques were offered as a novel method for resolving complicated and multidimensional situations. Heuristic and metaheuristic algorithms are two prominent subcategories of these. Metaheuristic approaches are utilized for a variety of challenging and intricate optimal problems, while heuristic techniques are employed for local traps and solving specific optimal issues. Exploring and profiting are both goals of metaheuristic. This approach initially uses exploration to find solutions before moving on to exploitation, which increases the precision of the exploration phase. The use of metaheuristics in continuous, discrete, and optimization has increased significantly. Intelligent beings and organisms in nature create these kinds of algorithms. Many of these metaheuristic algorithms have recently been presented, and one of them is known as “African Vulture Optimization Algorithm (AVOA).” This suggested a lifestyle modeled by African vultures. Based to the fundamental ideas regarding vultures, the AVOA method is going to be developed in a step-by-step manner, with every requirement met and points defined in each stage. There are four phases in the AVOA technique: phases 1, 2, 3, and 4. Phase 1 is used to identify the best vultures for each group, Phase 2 is used to determine the pace at which vultures starve, Phase 3 is used for exploration, and Phase 4 is used for exploitation. African vulture algorithm for optimization holds optimization employing these stages. Consequently, we anticipate that the “African vulture optimization algorithm” will produce greater outcomes than any other algorithm that has been presented so far.