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Maryam Fadavian

Publications and source records attributed to Maryam Fadavian.

2 recordsLinked to original sources
arXiv2022

A heuristic algorithm for straight-line embedding of a hamiltonian cycle onto a given set of points inside simple polygons

This paper investigated the problem of embedding a simple Hamiltonian Cycle with n vertices on n points inside a simple polygon. This problem seeks to embed a straight-line cycle (without bends), which does not intersect either itself or the sides of the polygon, i.e., it is planar. This problem is a special case of an open problem to find a simple Hamiltonian (s, X, t)-path (a simple path that starts at s and ends at t, where s, t, and all other vertices within the path are a member of set X) inside a simple polygon, which does not intersect itself or the sides of the polygon. The complexity of the problem in this paper is not verified yet, and it is an open problem. However, similar problems are resolved that are NP-Complete. A heuristic algorithm with time complexity of O(r(n2m + n3)) and space complexity of O(n2 + m) is proposed to solve the problem.

cs.CG↗
arXiv2022

A genetic algorithm for straight-line embedding of a cycle onto a given set of points inside simple polygons

In this paper, we have examined the problem of embedding a cycle of n vertices onto a given set of n points inside a simple polygon. The goal of the problem is that the cycle must be embedded without bends and does not intersect itself and the polygon. This problem is a special case of the open problem of finding a (s, X, t) - simple Hamiltonian path inside a simple polygon that does not intersect itself and the sides of the polygon. The complexity of the problem is examined in this paper is open, but it has been proved that similar problems are NP-complete. We have presented a metaheuristic algorithm based on a genetic algorithm for straight-line embedding of a cycle with the minimum numbers of intersections, onto a given set of points inside simple polygons. The efficiency of the proposed genetic algorithm is due to the definition of the mutation operation, which removes it if there is an intersection between the embedded edges of the cycle. The experimental results show that the results of the version of the algorithm that uses this mutation operation are much more efficient than the version that uses only the usual two-points mutation operation.

cs.CG↗