Jalal eddin Aghazadeh heris - Faculty of Mathematics and Computer Science Allameh Tabataba’i University Tehran, Iran
Mohammadreza Asgari Oskoei - Faculty of Mathematics and Computer Science Allameh Tabataba’i University Tehran, Iran

Genetic algorithm is applicable to a wide range of constraint satisfaction problems such as n-queens problem. In the absence of specialized solution for a particular problem, geneticalgorithm would be efficient. But holism and random choices cause problem for genetic algorithm in searching large statespaces. So, the efficiency of this algorithm would be demoted when the size of state space of the problem grows exponentially. In this paper, we attempt to cover this weakness by using local search algorithm like minimal conflicts algorithm. Minimal conflicts algorithm is trying to provide partial view for geneticalgorithm by locally searching the state space. This may cause genetic algorithm to take longer steps toward the solution.Modified genetic algorithm, is the result of collaboration between genetic algorithm and minimal conflicts algorithm. Comparingthe results of applying standard genetic algorithm and modified genetic algorithm on n-queens problem in section VI, indicates the amount of performance improvement

genetic algorithm; minimal conflicts algorithm; nqueens problem;