A Novel Hybrid Approach to N-Queen Problem
These days computers deals with highly intricate problems. This paper also discusses such kind of complex problems called Constraint Satisfaction Problems (CSP). These problems have a set of variables, domain from which a variable takes its value and a set of constraints applied on these variables. For example N-Queen problem, timetabling problem, scheduling problem etc. are CSPs. In practical scenario, it is unlikely to obtain a solution that satisfies all constraints or most of the constraints. Such a solution is an exact solution. Even if an exact algorithm can be developed its time or space complexity may turnout unacceptable. In reality, it is often sufficient to find an approximate or partial solution to such NP problems using heuristic algorithms. Heuristic methods are used to speed up the process of finding a satisfactory solution, where an exhaustive search is impractical; hence resulting in guaranteed and approximate solutions. This paper proposes an efficient hybrid solution for standard N-Queen problem using Ant Colony Optimization and Genetic Algorithm. It also compares the performances of classical backtrack and brute force methods and heuristic methods, Simulated annealing and Genetic algorithm on N-Queen problem.
KeywordsConstraint Satisfaction Problems N-Queen Hybridized Heuristic Ant Colony Optimization (ACO) Genetic Algorithm (GA)
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