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Ant-Based Algorithms, particularly “Ant Colony Optimization (ACO)", can be described mathematically by modeling the behavior of artificial ants traversing a graph. The graph \( G = (V, E) \) represents the problem, where \( V \) is the set of vertices (nodes) and \( E \) is the set of edges (paths between nodes). Each edge \( (i, j) \in E \) has an associated pheromone level \( \tau _{ij}(t) \) and a heuristic value \( \eta _{ij} \) , which guide the ants in constructing solutions.

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Medical Image Processing

  • 章节

  • 发表日期：

    2025年

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  • Sumati Kumari Panda,
  • Velusamy Vijayakumar,
  • Ravi P. Agarwal

摘要

Ant-Based Algorithms, particularly “Ant Colony Optimization (ACO)", can be described mathematically by modeling the behavior of artificial ants traversing a graph. The graph \( G = (V, E) \) represents the problem, where \( V \) is the set of vertices (nodes) and \( E \) is the set of edges (paths between nodes). Each edge \( (i, j) \in E \) has an associated pheromone level \( \tau _{ij}(t) \) and a heuristic value \( \eta _{ij} \) , which guide the ants in constructing solutions.