Classical Optimization Problem Solution using Nature Inspired Algorithm

In this work a nature inspired algorithm is introduced to solve classical optimization problems. Ant Traversing Method (ATM) is implemented in this work to a typical NXN chessboard for N-Queens problem. In ATM is a set of intelligent Ant called Ant Agents are introduced to find the optimal solution for N_Queen problem. Agents work independently to find the result. First queen would be placed at any position, an Ant Agent starts its journey through the path of a Queen. The journey path of the Ant Agent would be blocked for other Queens. Unblocked cells of the chessboard would be considered as candidate position for the Queens. The chessboard cells would be blocked by depositing pheromone from the Ant Agent. Effectiveness and optimality of the proposed method are compared with existing methods by experimental results. Experimental outcome proves that our suggested approach attains an optimal outcome with less computation time than traditional backtracking, obtaining an optimal placement with an execution time of 11.98 ms for N=20. This enhancement proves the effectiveness of proposed ATM in solving large-scale problems.