optimal reservoir operation using deterministic adaptive refinement mechanism for ant algorithm

ant colony optimisation (aco) algorithm and adaptive refinement mechanism are used in this paper for solution of optimization problems. many of the real engineering problems are، however، of continuous nature and finding their solution by discrete ant based algorithms requires discretisation of the decision variables in which affected the convergence and performance of the algorithm. in this paper an adaptive refinement mechanism is suggested to improve the performance of ant algorithms in solving continuous optimization problems. the proposed mechanism is an iterative method in which the search space of the problem at each iteration is limited to a small range around the optimal solution obtained in previous iteration. the application of the proposed mechanism to solve some benchmark function optimization problems and reservoir operation problem is considered and the results are presented.compression of the results indicate the efficiency and effectiveness of the proposed method to improve the performance of the ant algorithms for continuous optimization problems.