Ahmed, Z. H. (2015a). A multi-parent genetic algorithm for the quadratic assignment problem. OPSEARCH, 52(4), 714–732.
Ahmed, Z. H. (2015b). An improved genetic algorithm using adaptive mutation operator for the quadratic assignment problem. 38th International Conference on Telecommunications and Signal Processing (TSP), 2015, 1–5. IEEE.
Anderson, E. J. (1996). Mechanisms for local search. European Journal of Operational Research, 88(1), 139–151.
Arkin, E. M., Hassin, R., & Sviridenko, M. (2001). Approximating the maximum quadratic assignment problem. Information Processing Letters, 77(1), 13–16.
Asarry, A., Zain, M. Z. M., Mailah, M., & Hussein, M. (2013). Suppression of hand tremor model using active force control with Particle swarm optimization and differential evolution. International Journal of Innovative Computiong, Information and Control, 9(9), 3759–3777.
Azarbonyad, H., & Babazadeh, R. (2014). A Genetic Algorithm for solving Quadratic Assignment Problem(QAP). Computing Research Repository, abs/1405.5050.
Balakrishnan, J., & Cheng, C. H. (2000). Genetic search and the dynamic layout problem. Computers and Operations Research, 27(6), 587–593.
Banzhaf, W. (1990). The “molecular” traveling salesman. Biological Cybernetics, 64(1), 7–14.
Battiti, R., & Tecchiolli, G. (1994). Simulated annealing and tabu search in the long run: A comparison on QAP tasks. Computer and Mathematics with Applications, 28(6), 1–8.
Bazaraa, M. S., & Sherali, H. D. (1982). On the Use of Exact and Heuristic Cutting Plane Methods for the Quadratic Assignment Problem. The Journal of the Operational Research Society, 33(11), 991–1003.
Brixius, N. W., & Anstreicher, K. M. (2000). Solving Quadratic Assignment Problems Using Convex Quadratic Programming Relaxations. Optimization Methods and Software, 16, 49–68.
Burkard, R. E., Dell’Amico, M., & Martello, S. (2009). Assignment Problems. Philadelphia: Society for Industrial and Applied Mathematics.
Burkard, R. E., Karisch, S. E., & Rendl, F. (1997). QAPLIB – A Quadratic Assignment Problem Library. Journal of Global Optimization, 10(4), 391–403.
Burkard, R. E., & Rendl, F. (1984). A thermodynamically motivated simulation procedure for combinatorial optimization problems. European Journal of Operational Research, 17(2), 169–174.
Clausen, J., & Perregaard, M. (1997). Solving Large Quadratic Assignment Problems in Parallel. Computational Optimization and Applications, 8(2), 111–127.
Connolly, D. T. (1990). An improved annealing scheme for the QAP. European Journal of Operational Research, 46(1), 93–100.
Consoli, S., Moreno-Pérez, J. A., Darby-Dowman, K., & Mladenovic, N. (2010). Discrete Particle Swarm Optimization for the minimum labelling Steiner tree problem. Natural Computing, 9(1), 29–46.
Czapiński, M. (2013). An effective Parallel Multistart Tabu Search for Quadratic Assignment Problem on CUDA platform. Journal of Parallel and Distributed Computing, 73(11), 1461–1468.
Day, R. O., Kleeman, M. P., & Lamont, G. B. (2003). Solving the multi-objective quadratic assignment problem using a fast messy genetic algorithm. Proceedings of Congress Evolutionary Computation (CEC ’03), 4, 2277–2283.
De, A., Bhattacharjee, A. K., Chanda, C. K., & Maji, B. (2012). Hybrid particle swarm optimization with wavelet mutation based segmentation and progressive transmission technique for MRI images. International Journal of Innovative Computing, Information and Control, 8(7), 5179–5197.
Drezner, Z. (2005). The extended concentric tabu for the quadratic assignment problem. European Journal of Operational Research, 160(2), 416–422.
Drezner, Z. (2008). Extensive experiments with hybrid genetic algorithms for the solution of the quadratic assignment problem. Computers & Operations Research, 35(3), 717–736.
Drezner, Z., & MisevicIus, A. (2013). Enhancing the performance of hybrid genetic algorithms by differential improvement. Computers & Operations Research, 40(4), 1038–1046.
Eberhart, R. C., & Shi, Y. (2001). Particle swarm optimization: developments, applications and resources. Evolutionary Computation, 2001. Proceedings of the 2001 Congress on, 1, 81–86. IEEE.
Fleurent, C., & Glover, F. (1999). Improved Constructive Multistart Strategies for the Quadratic Assignment Problem Using Adaptive Memory. INFORMS Journal on Computing, 11(2), 198–204.
Gambardella, L. M., Taillard, É. D., & Dorigo, M. (1999). Ant Colonies for the Quadratic Assignment Problem. The Journal of the Operational Research Society, 50(2), 167–176.
Garey, M. R., & Johnson, D. S. (1979). Computers and Intractability: A Guide to the Theory of NP-Completeness. New York, NY, USA: W. H. Freeman & Co.
Goldberg, D. E., & Lingle Jr., R. (1985). Alleles, loci, and the traveling salesman problem. In J. J. Grefenstette (Ed.), Proceedings of the First International Conference on Genetic Algorithms and Their Applications. Lawrence Erlbaum Associates, Publishers.
Hafiz, F., & Abdennour, A. (2016). Particle Swarm Algorithm variants for the Quadratic Assignment Problems-A probabilistic learning approach. Expert Systems with Applications, 44, 413–431.
Hahn, P. M., Hightower, W. L., Johnson, T. A., Guignard-Spielberg, M., & Roucairol, C. (2001). Tree elaboration strategies in branch and bound algorithms for solving the quadratic assignment problem. Yugoslav Journal of Operational Research, 11(1), 41–60.
Hassin, R., Levin, A., & Sviridenko, M. (2009). Approximating the minimum quadratic assignment problems. ACM Transactions on Algorithms, 6(1), 18:1–18:10.
Hong, G. (2013). A Hybrid Ant Colony Algorithm for Quadratic Assignment Problem. The Open Electrical and Electronic Engineering Journal, 7, 51–54.
Izakian, H., Ladani, B. T., Abraham, A., & Snášel, V. (2010). A Discrete Particle Swarm Optimization Approach for Grid Job Scheduling. International Journal of Innovative Computing, Information and Control, 6(9), 1–15.
James, T., Rego, C., & Glover, F. (2009). A cooperative parallel tabu search algorithm for the quadratic assignment problem. European Journal of Operational Research, 195, 810–826.
Kennedy, J., & Eberhart, R. C. (1995). Particle swarm optimization. Proceedings of the IEEE International Conference on Neural Networks, 1942–1948.
Koopmans, T. C., & Beckmann, M. (1957). Assignment problems and the location of economic activities. Econometrica, 25, 53–76.
Li, & Smith, J. M. (1995). Theory and Methodology: An algorithm for Quadratic Assignment Problems. European Journal of Operational Research, 81, 205–216.
Lian, Z., Lin, W., Gao, Y., & Jiao, B. (2014). A Discrete Particle Swarm Optimization Algorithm for Job-shop Scheduling Problem to Maximizing Production. International Journal of Innovative Computing, Information and Control, 10(2), 729–740.
Liu, H., & Abraham, A. (2007). A Hybrid Fuzzy Variable Neighborhood Particle Swarm Optimization Algorithm. Journal of Universal Computer Science, 13.
Loiola, E. M., Abreu, N. M. M. de, Boaventura-Netto, P. O., Hahn, P., & Querido, T. (2007). A survey for the quadratic assignment problem. European Journal of Operational Research, 176(2), 657–690.
Loiola, E. M., Maria, N., Abreu, M., Boaventura-netto, P. O., Hahn, P., & Querido, T. (2004). An Analytical Survey for the Quadratic Assignment Problem. Council for the Scientific and Technological Development, of the Brazilian Gov.
Mamaghani, A. S., & Meybodi, M. R. (2012). Solving the Quadratic Assignment Problem with the modified hybrid PSO algorithm. Proceedings of 6th International Conference on Application of Information and Communication Technologies (AICT), 1–6.
Matsui, S., Kobayashi, Y., Watanabe, K., & Horio, Y. (2004). Exponential chaotic tabu search hardware for quadratic assignment problems using switched-current chaotic neuron IC. Proceedings of IEEE Internationa Joint Conference on Neural Networks, 3, 2221–2225.
Misevicius, A. (2000). An Intensive Search Algorithm for the Quadratic Assignment Problem. Informatica, 11(2), 145–162.
Misevicius, A. (2003). A Modified Simulated Annealing Algorithm for the Quadratic Assignment Problem. Informatica, 14(4), 497–514.
Misevicius, A. (2004). An improved hybrid optimization algorithm for the quadratic assignment problem. Mathematical Modelling and Analysis, 9(2), 149–168.
Misevicius, A., & Guogis, E. (2012). Computational study of four genetic algorithm variants for solving the quadratic assignment problem. International Conference on Information and Software Technologies, 24–37. Springer.
Osman, I. H., & Laporte, G. (1996). Metaheuristics: A bibliography. Annals of Operations Research, 63(5), 511–623.
Ozsoydan, F. B., & Sarac, T. (2011). A Discrete Particle Swarm Optimization Algorithm for Bi-Criteria Warehouse Location Problem. Istanbul University Econometrics and Statistics e-Journal, 13(1), 114–124.
Pan, Q.-K., Tasgetiren, M. F., & Liang, Y.-C. (2008). A discrete particle swarm optimization algorithm for the no-wait flowshop scheduling problem. Computers and Operations Research, 35(9), 2807–2839.
Paul, G. (2011). An efficient implementation of the simulated annealing heuristic for the quadratic assignment problem. Computing Research Repository, abs/1111.1353.
Paul, G. (2012). A GPU implementation of the Simulated Annealing Heuristic for the Quadratic Assignment Problem. Computing Research Repository, abs/1208.2675.
Peng, H., Zhang, Z., Wang, J., & Shi, P. (2013). Audio watermarking framework using multi-objective particle swarm optimization. International Journal of Innovative Computing, Information and Control, 9(7), 2789–2800.
Peng, T., Huanchen, W., & Dongme, Z. (1996). Simulated Annealing for the Quadratic Assignment Problem: A further study. Computers and industrial Engineering, 31(3/4), 925–928.
Pradeepmon, T. G., Panicker, V. V., & Sridharan, R. (2016). Parameter Selection of Discrete Particle Swarm Optimization Algorithm for the Quadratic Assignment Problems. Procedia Technology, 25, 998–1005.
Ramkumar, A. S., Ponnambalam, S. G., Jawahar, N., & Suresh, R. K. (2008). Iterated fast local search algorithm for solving quadratic assignment problems. Robotics and Computer-Integrated Manufacturing, 24(3), 392–401.
Rapai, M. R., Kanovi, Ž., & Jelici, Z. D. (2008). Discrete particle swarm optimization algorithm for solving optimal sensor deployment problem. Journal of Automatic Control, 18(1), 9–14.
See, P. C., & Wong, K. Y. (2008). Application of ant colony optimisation algorithms in solving facility layout problems formulated as quadratic assignment problems: a review. International Journal of Industrial and Systems Engineering, 3(6), 644–672.
Sevkli, F. Mehmet Mamedsaidov Ruslan Camci. (2014). A novel discrete particle swarm optimization for p-median problem. Journal of King Saud University - Engineering Sciences, 26(1), 11–19.
Skorin-Kapov, J. (1990). Tabu search applied to the quadratic assignment problem. ORSA Journal on Computing, 2(1), 33–45.
Song, L. Q., Lim, M. H., & Ong, Y. S. (2011). Neural meta-memes framework for managing search algorithms in combinatorial optimization. IEEE Workshop on Memetic Computing (MC), 2011, 1–6.
Syswerda, G. (1991). Schedule Optimization Using Genetic Algorithms. In L. Davis (Ed.), Handbook of Genetic Algorithms. New York, NY: Van Nostrand Reinhold.
Szwed, P., & Chmiel, W. (2015). Multi-swarm PSO algorithm for the Quadratic Assignment Problem: a massive parallel implementation on the OpenCL platform. arXiv preprint arXiv:1504.05158.
Szwed, P., Chmiel, W., & Kadłuczka, P. (2015). OpenCL Implementation of PSO Algorithm for the Quadratic Assignment Problem. Artificial Intelligence and Soft Computing, 223–234. Springer.
Talbi, E. G., Hafidi, Z., & Geib, J.-M. (1998). A parallel adaptive tabu search approach. Parallel Computing, 24(14), 2003–2019.
Tasgetiren, M. F., Liang, Y.-C., Sevkli, M., & Gencyilmaz, G. (2006). Particle swarm optimization and differential evolution for the single machine total weighted tardiness problem. International Journal of Production Research, 44(22), 4737–4754.
Tate, D. M., & Smith, A. E. (1995). A genetic approach to the quadratic assignment problem. Computers and Operations Research, 22(1), 73–83.
Tosun, U. (2014). A New Recombination Operator for the Genetic Algorithm Solution of the Quadratic Assignment Problem. Procedia Computer Science, 32(0), 29–36.
Tseng, & Liang, S. C. (2006). A Hybrid Metaheuristic for the Quadratic Assignment Problem. Computational Optimization and Applications, 34, 85–113.
Urban, T. L. (1998). Solution procedures for the dynamic facility layout problem. Annals of Operations Research, 76(0), 323–342.
Uwate, Y., Nishio, Y., Ueta, T., Kawabe, T., & Ikeguchi, T. (2004). Performance of Chaos and Burst Noises Injected to the Hopfield NN for Quadratic Assignment Problems. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, E87-A(4), 937–943.
Wakabayashi, S., Kimura, Y., & Nagayama, S. (2006). FPGA implementation of tabu search for the quadratic assignment problem. Proceedings of IEEE International Conference on Field Programmable Technology (FPT 2006), 269–272.
West, D. H. (1983). Algorithm 608: Approximate Solution of the Quadratic Assignment Problem. ACM Transactions on Mathematical Software, 9(4), 461–466.
Wilhelm, M. R., & Ward, T. L. (1987). Solving Quadratic Assignment Problems by ‘Simulated Annealing. IIE Transactions, 19(1), 107–119.
Wu, Y., & Ji, P. (2007). Solving the quadratic assignment problems by a genetic algorithm with a new replacement strategy. International Journal of Humanities and Social Science, 151–155.
Xia, Y. (2010). An efficient continuation method for quadratic assignment problems. Computers and Operations Research, 37(6), 1027–1032.
Zaied, A. N. H., & Shawky, L. A. E.-F. (2014). A Survey of the Quadratic Assignment Problem. International Journal of Computer Applications, 101(6), 28–36.
Zhang, Y., Wang, S., & Ji, G. (2015). A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications. Mathematical Problems in Engineering, 1–38.
Zhu, W., Curry, J., & Marquez, A. (2010). SIMD tabu search for the quadratic assignment problem with graphics hardware acceleration. International Journal of Production Research, 48(4), 1035–1047.