螞蟻演算法(Ant Algorithms)為近年來廣被探討的一種巨集啟發式方法，也被統稱為螞蟻群落最佳化(Ant Colony Optimization, ACO)方法。ACO已被成功應用於求解許多複雜的組合最佳化問題上，並衍生出多種不同的執行機制(例如：AS、ACS、Ant-Q、Max-Min AS與ASrank)。這些ACO方法的主要差異在於兩個部份：路徑構建機制與費洛蒙更新機制。本研究之目的即針對ACO的路徑構建機制及其控制參數設定進行深入研究，提出一個稱之為「調適型螞蟻演算法(Adaptive A The Ant Algorithm, also named as Ant Colony Optimization (ACO), is recently a famous meta-heuristic approach that has been successfully applied to solve many complicated Combinatorial Optimization Problems. Furthermore, several variants of the Ant Algorit
