International Journal of Computer Science & Network Security

국제컴퓨터통신보호논문지학회 (International Journal of Computer Science & Network Security)
권호 표지
DOI QR코드

DOI QR Code

Searching Algorithms Implementation and Comparison of Romania Problem

  • Ismail. A. Humied (Computer Science, Faculty of Police, Policy Academic, Ministry of interior)
  • 투고 : 2024.09.05
  • 발행 : 2024.09.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Nowadays, permutation problems with large state spaces and the path to solution is irrelevant such as N-Queens problem has the same general property for many important applications such as integrated-circuit design, factory-floor layout, job-shop scheduling, automatic programming, telecommunications network optimization, vehicle routing, and portfolio management. Therefore, methods which are able to find a solution are very important. Genetic algorithm (GA) is one the most well-known methods for solving N-Queens problem and applicable to a wide range of permutation problems. 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, the new method presented based on genetic algorithm to cover this weakness. This new method is trying to provide partial view for genetic algorithm by locally searching the state space. This may cause genetic algorithm to take shorter steps toward the solution. To find the first solution and other solutions in N-Queens problem using proposed method: dividing N-Queens problem into subproblems, which configuring initial population of genetic algorithm. The proposed method is evaluated and compares it with two similar methods that indicate the amount of performance improvement.

키워드

참고문헌

  1. X. Hu, R. C. Eberhart, and Y. Shi, "Swarm intelligence for permutation optimization: a case study of n-queens problem", Proceedings of the IEEE Swarm Intelligence Symposium (SIS '03), pp. 243-246, Indianapolis, Ind, USA, April 2003.
  2. Stuart j. Russell and Peter Norvig, "Artificial Intelligence A Modern Approach", (3 rd Edition), Prentice Hall, 2010.
  3. I. Martinjak and M. Golub, "Comparison of Heuristic Algorithms for the N-Queen Problem", Proceedings of the 29th International Conference on Information Technology Interfaces , ITI 2007, pp. 759-764, Cavtat, Croatia, June 25-28,2007.
  4. K. D. Crawford, "Solving the N-Queens Problem Using Genetic Algorithms", In Proceedings ACM/SIGAPP Symposium on Applied Computing,Kansas City, pp. 1039-1047, 1992.
  5. S. Khan, M. Bilal, M. Sharif, M. Sajid and R. Baig, "Solution of n-Queen Problem Using ACO" Multitopic Conference, 2009. INMIC 2009. IEEE 13th International , Islamabad, pp. 1 - 5, 14-15 Dec. 2009.
  6. J. Turner, A. Homaifar, S. Ali, "The n-queens problem and genetic algorithms", in IEEE, pp. 262-267, 1992.
  7. M. Boiikovic, M. Golub, L. Budin, "Solving n-Queen problem using global parallel genetic algorithm", in IEEE, pp. 104 - 107, vol.2, 2003.
  8. A. M. Turky, M. S. Ahmad "Using Genetic Algorithm for Solving N -Queens Problem", in IEEE, pp. 745-747, 2010.
  9. A. Amooshahi, M. Joudaki, M. Imani and N. Mazhari, "Presenting a new method based on cooperative PSO to solve permutation problems: A case study of n-queen problem", in IEEE, pp. 218-222, 2011.
  10. R. G. Sharma, B. Keswani, "implementation of n-queens puzzle using meta-heuristic algorithm (cuckoo search)", in International Journal of Latest Trends in Engineering and Technology, pp. 343- 347, vol. 2, 2013.
  11. J. E. A. heris and M. A. Oskoei, "Modified Genetic Algorithm for Solving n-Queens Problem", in IEEE, 2014.
  12. "D. Whitley, "a genetic algorithm tutorial", statistics and computing, pp. 65-85, 1994".
  13. J. Bell, B. Stevens, "A survey of known results and research areas for n-queens", Discrete Mathematics 309, pp. 1-31, 2009.