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Population-based Ant Colony algorithm is stochastic local search algorithm that mimics the behavior of
real ants, simulating pheromone trails to search for solutions to combinatorial optimization problems. This
paper introduces population-based Ant Colony algorithm to solve 3D Hydrophobic Polar Protein structure
Prediction Problem then introduces a new enhanced approach of population-based Ant Colony algorithm
called Enhanced Population-based Ant Colony algorithm (EP-ACO) to avoid stagnation problem in
population-based Ant Colony algorithm and increase exploration in the search space escaping from local
optima, The experiments show that our approach appears more efficient results than state of art method.