A GA-ACO-local search hybrid algorithm for solving quadratic assignment problem

GECCO 2006 - Genetic and Evolutionary Computation Conference

Volumn 1, Issue , 2006, Pages 599-605

  Xu, Yi Liang ^a   Lim, Meng Hiot ^a   Ong, Yew Soon ^a   Tang, Jing ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Adaptive Parameter Control; Ant Colony Optimization; Genetic Algorithm; Hybrid Algorithm; Local Search

Indexed keywords

COMPUTATIONAL METHODS; CONVERGENCE OF NUMERICAL METHODS; HEURISTIC METHODS; ONLINE SEARCHING; OPTIMIZATION; PROBLEM SOLVING;

ADAPTIVE PARAMETER CONTROL; ANT COLONY OPTIMIZATION (ACO); HYBRID ALGORITHMS; META HEURISTICS; QUADRATIC ASSIGNMENT PROBLEM (QAP);

GENETIC ALGORITHMS;

EID: 33750246102     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1143997.1144103     Document Type: Conference Paper

References (29)

1. Stützle, T. Iterated local search for the quadratic assignment problem, European Journal of Operational Research, in press, corrected proof, available online 13 May, 2005.
2. Lim, M.H., Yuan, Y. and Omatu, S. Efficient genetic algorithms using simple genes exchange local search policy for the quadratic assignment problem. Computational Optimization and Applications, 2000;15:249-268.
3. Lim, M.H., Yuan, Y. and Omatu, S. Extensive testing of a hybrid genetic algorithm for quadratic assignment problem. Computational Optimization and Applications, 2002;23:47-643.
4. Drezner, Z. A new genetic algorithm for the Quadratic Assignment Problem. INFORMS J. Comput., 15, (2003), 320-330.
5. Ahuja, R.K., Orlin, J.B., and Tiwari, A. A greedy genetic algorithm for the Quadratic Assignment Problem. Computers and Operations Research, 27, (2000), 917-934.
6. Koopmans, T.C. and Beckmann, M.J. Assignment problems and the location of economic activities. Econometrica, 25, (1957), 53-76.
7. Steinberg, L. The backboard wiring problem: a placement algorithm. SIAM Rev, 3, (1961), 37-50.
8. Dickey, J.W. and Hopkins, J.W. Campus building arrangement using TOPAZ. Transportation Rev. 6, (1972), 59-68.
9. Krarup, J. and Pruzan, P.M. Computer-aided layout design. Math. Programming Study, 9, (1978), 85-94.
10. Elshafei, A.N. Hospital layout as quadratic assignment problem. Operational Res. Quarterly, 28, (1977), 167-179.
11. Tate, D.M. and Smith, A.E. A genetic approach to the quadratic assignment problem. Computer & Operations Research, 22, 1 (1995), 73-83.
12. Li, Y., Pardalos, P.M. and Resende, M. A greedy randomized adaptive search procedure for the quadratic assignment problem. In Quadratic Assignment and Related Problems. P. Pardalos and H. Wolkowicz (Eds.), AMS: Providence, Rhode Island, DIMACS Series in Discrete Mathematics and Theoretical Computer Science. 1994; 16:173-187.
13. Burkard, R.E. and Rendl, F. A thermodynamically motivated simulation procedure for combinatorial optimization problems. European Journal of Operational Research, 17, (1984), 169-174.
14. Connolly, D.T. An improved annealing scheme for the QAP. European Journal of Operational Research, 46, (1990), 93-100.
15. Laursen, P.S. Simulated annealing for the QAP-optimal tradeoff between simulation time and quality. European Journal of Operational Research, 63, (1993), 238-243.
16. Chakrapani, J. and Skorin-Kapov, J. A connectionist approach to the quadratic assignment problem. Computers & Operations Research, 19, 13-14 (1992), 287-295.
17. Skorin-Kapov, J. Extensions of a tabu search adaption to the quadratic assignment problem. Computer & Operations Research, 21, 8 (1994), 855-865.
18. Taillard, E. Robust taboo search for the quadratic assignment problem. Parallel Computing, 17, (1991), 443-455.
19. Brown, D.E., Huntley, C.L. and Spillane, A.R. A parallel genetic heuristic for the quadratic assignment problem. In Proceedings of International Conference on Genetic Algorithms. 1989, 406-415.
20. Fleurent, C. and Ferland, J. Genetic hybrids for the quadratic assignment problem. In Quadratic Assignment and Related Problems. P. Pardalos and H. Wolkowicz (Eds.), AMS: Providence, Rhode Island, DIMACS Series in Discrete Mathematics and Theoretical Computer Science. 1994; 16:173-187.
21. Merz, P. and Freislenben, B. A genetic local search approach to the quadratic assignment problem. In Proceedings of International Conference on Genetic Algorithms (ICGA '97). Morgan Kaufmann: San Mateo, CA, 1997, 465-472.
22. Burkard, R.E., Karisch, S.E. and Rendl, F. QAPLIB - A quadratic assignment problem library. Journal of Global Optimization, 10, (1997), 391-403.
23. Maniezzo, V. and Colorni, A. The ant system applied to the Quadratic Assignment Problem. IEEE Transaction on Knowledge and Data Engineering, 11, 5, (1999), 769-778.
24. Stützle, T. MAX-MIN ant system for Quadratic Assignment Problem. Technical Report AIDA-97-04, Intellectics Group, Department of Computer Science, Darmstadt University of Technology, Germnay, July 1997.
25. Stützle, T. and Hoos, H. H. MAX-MIN ant system. Future Generation Computer Systems, 16, 8, (2000), 889-914.
26. Ong, Y. S., Lim, M. H., Zhu, N. and Wong, K. W. Classification of Adaptive Memetic Algorithms: A Comparative Study. IEEE Transactions on Systems, Man and Cybernetics - Part B, 36, 1, (2006).
27. Ong, Y. S. and Keane, A. J. Meta-Lamarckian Learning in Memetic Algorithm. IEEE Transactions On Evolutionary Computation, 8, 2, (2004), 99-110.
28. Acan, A. GAACO: A GA + ACO Hybrid for Faster and Better Search Capability. In Proceedings of Third International Workshop on Ant Algorithms (ANTS'02). Brussels, Belgium, 2002, 300-301.
29. Reimann, M., Shtovba, S. and Nepomuceno, E. A hybrid ACO-GA approach to solve Vehicle Routing Problems, Student Papers of the Complex Systems Summer School, Budapest, Santa Fe Institute, (2001).