Asian Journal of Mathematics and Computer Research

Constraint satisfaction algorithms have rapidly gained popularity for solving a wide range of problems. The algorithm finds all possible solutions for as long as it satisfies the stated constraints. Although, satisfactory algorithm is usually a combination of both satisfactory and optimal solutions. However, the earlier developed SEBJSolver algorithm based on Constraint satisfaction (CS) does not specifically determine preferred solution and also requires large amount of memory as the problem becomes larger. In this paper, we presented SEBJSolver2 which is an extended version of SEBJSolver to enable finding optimal solution to problems thereby minimising the memory and also improves the cost performance of the algorithm in finding solution to problem. The experimental results obtained in this study shows that the extended algorithm is more efficient and also indicates fewer memory utilization when compared with the previous one.