Title :
Modified genetic algorithm for solving n-queens problem
Author :
Heris, Jalal Eddin Aghazadeh ; Oskoei, Mohammadreza Asgari
Author_Institution :
Fac. of Math. & Comput. Sci., Allameh Tabataba´i Univ., Tehran, Iran
Abstract :
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, genetic algorithm would be efficient. But holism and random choices cause problem for genetic algorithm in searching large state spaces. 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 genetic algorithm 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. Comparing the results of applying standard genetic algorithm and modified genetic algorithm on n-queens problem in section VI, indicates the amount of performance improvement.
Keywords :
computational complexity; constraint satisfaction problems; genetic algorithms; search problems; state-space methods; NP problem; constraint satisfaction problems; local search algorithm; minimal conflicts algorithm; modified genetic algorithm; n-queens problem solving; state space search; Algorithm design and analysis; Arrays; Genetic algorithms; Search problems; Sociology; Standards; Statistics; genetic algorithm; minimal conflicts algorithm; n-queens problem;
Conference_Titel :
Intelligent Systems (ICIS), 2014 Iranian Conference on
Conference_Location :
Bam
Print_ISBN :
978-1-4799-3350-1
DOI :
10.1109/IranianCIS.2014.6802550