How to cite this paper
Hameed, A., Aboobaider, B., Mutar, M & Choon, N. (2020). A new hybrid approach based on discrete differential evolution algorithm to enhancement solutions of quadratic assignment problem.International Journal of Industrial Engineering Computations , 11(1), 51-72.
Refrences
Abdel-Baset, M., Wu, H., Zhou, Y., & Abdel-Fatah, L. (2017). Elite opposition-flower pollination algorithm for quadratic assignment problem. Journal of Intelligent & Fuzzy Systems, 33(2), 901-911.
Abdel-Basset, M., Manogaran, G., Rashad, H., & Zaied, A. N. H. (2018a). A comprehensive review of quadratic assignment problem: variants, hybrids and applications. Journal of Ambient Intelligence and Humanized Computing, 1-24. doi: 10.1007/s12652-018-0917-x.
Abdel-Basset, M., Manogaran, G., El-Shahat, D., & Mirjalili, S. (2018b). Integrating the whale algorithm with tabu search for quadratic assignment problem: a new approach for locating hospital departments. Applied Soft Computing, 73, 530-546.
Abdelkafi, O., Idoumghar, L., & Lepagnot, J. (2015). Comparison of two diversification methods to solve the quadratic assignment problem. Procedia Computer Science, 51, 2703-2707.
Ahmed, Z. H. (2018). A hybrid algorithm combining lexisearch and genetic algorithms for the quadratic assignment problem. Cogent Engineering, 5(1), 1423743.
Benlic, U., & Hao, J. K. (2013). Breakout local search for the quadratic assignment problem. Applied Mathematics and Computation, 219(9), 4800-4815.
Cela, E., Deineko, V., & Woeginger, G. J. (2018). New special cases of the Quadratic Assignment Problem with diagonally structured coefficient matrices. European journal of operational research, 267(3), 818-834.
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.
Tate, D. M., & Smith, A. E. (1995). A genetic approach to the quadratic assignment problem. Computers & Operations Research, 22(1), 73-83.
Doerner, K., Focke, A., & Gutjahr, W. J. (2007). Multicriteria tour planning for mobile healthcare facilities in a developing country. European Journal of Operational Research, 179(3), 1078-1096.
Duman, E., Uysal, M., & Alkaya, A. F. (2012). Migrating Birds Optimization: A new metaheuristic approach and its performance on quadratic assignment problem. Information Sciences, 217, 65-77.
Taillard, É. (1991). Robust taboo search for the quadratic assignment problem. Parallel computing, 17(4-5), 443-455.
Harris, M., Berretta, R., Inostroza-Ponta, M., & Moscato, P. (2015, May). A memetic algorithm for the quadratic assignment problem with parallel local search. In 2015 IEEE congress on evolutionary computation (CEC) (pp. 838-845). IEEE.
Kaviani, M., Abbasi, M., Rahpeyma, B., & Yusefi, M. (2014). A hybrid tabu search-simulated annealing method to solve quadratic assignment problem. Decision Science Letters, 3(3), 391-396.
Koopmans, T. C., & Beckmann, M. (1957). Assignment problems and the location of economic activities. Econometrica: journal of the Econometric Society, 25(1), 53-76.
Kushida, J. I., Oba, K., Hara, A., & Takahama, T. (2012, November). Solving quadratic assignment problems by differential evolution. In The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems(pp. 639-644). IEEE.
Lim, W. L., Wibowo, A., Desa, M. I., & Haron, H. (2016). A biogeography-based optimization algorithm hybridized with tabu search for the quadratic assignment problem. Computational intelligence and neuroscience, 2016, 27.
Lv, C. (2012, October). A hybrid strategy for the quadratic assignment problem. In 2012 International Conference on Information Management, Innovation Management and Industrial Engineering (Vol. 2, pp. 31-34). IEEE.
Kaviani, M., Abbasi, M., Rahpeyma, B., & Yusefi, M. (2014). A hybrid tabu search-simulated annealing method to solve quadratic assignment problem. Decision Science Letters, 3(3), 391-396.
Pan, Q. K., Tasgetiren, M. F., & Liang, Y. C. (2008). A discrete differential evolution algorithm for the permutation flowshop scheduling problem. Computers & Industrial Engineering, 55(4), 795-816.
Pradeepmon, T., Sridharan, R., & Panicker, V. (2018). Development of modified discrete particle swarm optimization algorithm for quadratic assignment problems. International Journal of Industrial Engineering Computations, 9(4), 491-508.
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.
Riffi, M. E., Saji, Y., & Barkatou, M. (2017). Incorporating a modified uniform crossover and 2-exchange neighborhood mechanism in a discrete bat algorithm to solve the quadratic assignment problem. Egyptian Informatics Journal, 18(3), 221-232.
Said, G. A. E. N. A., Mahmoud, A. M., & El-Horbaty, E. S. M. (2014). A comparative study of meta-heuristic algorithms for solving quadratic assignment problem. International Journal of Advanced Computer Science and Applications (IJACSA), 5(1), 1–6.
Shariff, S. R., Moin, N. H., & Omar, M. (2012). Location allocation modeling for healthcare facility planning in Malaysia. Computers & Industrial Engineering, 62(4), 1000-1010.
Şahinkoç, M., & Bilge, Ü. (2018). Facility layout problem with QAP formulation under scenario-based uncertainty. INFOR: Information Systems and Operational Research, 56(4), 406-427.
Samanta, S., Philip, D., & Chakraborty, S. (2018). Bi-objective dependent location quadratic assignment problem: Formulation and solution using a modified artificial bee colony algorithm. Computers & Industrial Engineering, 121, 8-26.
Scalia, G., Micale, R., Giallanza, A., & Marannano, G. (2019). Firefly algorithm based upon slicing structure encoding for unequal facility layout problem. International Journal of Industrial Engineering Computations, 10(3), 349-360.
Shukla, A. (2015, May). A modified bat algorithm for the quadratic assignment problem. In 2015 IEEE Congress on Evolutionary Computation (CEC) (pp. 486-490). IEEE.
Da Silva, G. C., Bahiense, L., Ochi, L. S., & Boaventura-Netto, P. O. (2012). The dynamic space allocation problem: Applying hybrid GRASP and Tabu search metaheuristics. Computers & Operations Research, 39(3), 671-677.
Syam, S. S., & Côté, M. J. (2010). A location–allocation model for service providers with application to not-for-profit health care organizations. Omega, 38(3-4), 157-166.
Tasgetiren, M. F., Pan, Q. K., Suganthan, P. N., & Dizbay, I. E. (2013, April). Metaheuristic algorithms for the quadratic assignment problem. In 2013 IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS) (pp. 131-137). IEEE.
Van Luong, T., Melab, N., & Talbi, E. G. (2010, July). Parallel hybrid evolutionary algorithms on GPU. In IEEE Congress on Evolutionary Computation (pp. 1-8). IEEE.
Xia, X., & Zhou, Y. (2018). Performance analysis of ACO on the quadratic assignment problem. Chinese Journal of Electronics, 27(1), 26-34.
Zhang, Y., Berman, O., Marcotte, P., & Verter, V. (2010). A bilevel model for preventive healthcare facility network design with congestion. IIE Transactions, 42(12), 865-880.
Abdel-Basset, M., Manogaran, G., Rashad, H., & Zaied, A. N. H. (2018a). A comprehensive review of quadratic assignment problem: variants, hybrids and applications. Journal of Ambient Intelligence and Humanized Computing, 1-24. doi: 10.1007/s12652-018-0917-x.
Abdel-Basset, M., Manogaran, G., El-Shahat, D., & Mirjalili, S. (2018b). Integrating the whale algorithm with tabu search for quadratic assignment problem: a new approach for locating hospital departments. Applied Soft Computing, 73, 530-546.
Abdelkafi, O., Idoumghar, L., & Lepagnot, J. (2015). Comparison of two diversification methods to solve the quadratic assignment problem. Procedia Computer Science, 51, 2703-2707.
Ahmed, Z. H. (2018). A hybrid algorithm combining lexisearch and genetic algorithms for the quadratic assignment problem. Cogent Engineering, 5(1), 1423743.
Benlic, U., & Hao, J. K. (2013). Breakout local search for the quadratic assignment problem. Applied Mathematics and Computation, 219(9), 4800-4815.
Cela, E., Deineko, V., & Woeginger, G. J. (2018). New special cases of the Quadratic Assignment Problem with diagonally structured coefficient matrices. European journal of operational research, 267(3), 818-834.
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.
Tate, D. M., & Smith, A. E. (1995). A genetic approach to the quadratic assignment problem. Computers & Operations Research, 22(1), 73-83.
Doerner, K., Focke, A., & Gutjahr, W. J. (2007). Multicriteria tour planning for mobile healthcare facilities in a developing country. European Journal of Operational Research, 179(3), 1078-1096.
Duman, E., Uysal, M., & Alkaya, A. F. (2012). Migrating Birds Optimization: A new metaheuristic approach and its performance on quadratic assignment problem. Information Sciences, 217, 65-77.
Taillard, É. (1991). Robust taboo search for the quadratic assignment problem. Parallel computing, 17(4-5), 443-455.
Harris, M., Berretta, R., Inostroza-Ponta, M., & Moscato, P. (2015, May). A memetic algorithm for the quadratic assignment problem with parallel local search. In 2015 IEEE congress on evolutionary computation (CEC) (pp. 838-845). IEEE.
Kaviani, M., Abbasi, M., Rahpeyma, B., & Yusefi, M. (2014). A hybrid tabu search-simulated annealing method to solve quadratic assignment problem. Decision Science Letters, 3(3), 391-396.
Koopmans, T. C., & Beckmann, M. (1957). Assignment problems and the location of economic activities. Econometrica: journal of the Econometric Society, 25(1), 53-76.
Kushida, J. I., Oba, K., Hara, A., & Takahama, T. (2012, November). Solving quadratic assignment problems by differential evolution. In The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems(pp. 639-644). IEEE.
Lim, W. L., Wibowo, A., Desa, M. I., & Haron, H. (2016). A biogeography-based optimization algorithm hybridized with tabu search for the quadratic assignment problem. Computational intelligence and neuroscience, 2016, 27.
Lv, C. (2012, October). A hybrid strategy for the quadratic assignment problem. In 2012 International Conference on Information Management, Innovation Management and Industrial Engineering (Vol. 2, pp. 31-34). IEEE.
Kaviani, M., Abbasi, M., Rahpeyma, B., & Yusefi, M. (2014). A hybrid tabu search-simulated annealing method to solve quadratic assignment problem. Decision Science Letters, 3(3), 391-396.
Pan, Q. K., Tasgetiren, M. F., & Liang, Y. C. (2008). A discrete differential evolution algorithm for the permutation flowshop scheduling problem. Computers & Industrial Engineering, 55(4), 795-816.
Pradeepmon, T., Sridharan, R., & Panicker, V. (2018). Development of modified discrete particle swarm optimization algorithm for quadratic assignment problems. International Journal of Industrial Engineering Computations, 9(4), 491-508.
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.
Riffi, M. E., Saji, Y., & Barkatou, M. (2017). Incorporating a modified uniform crossover and 2-exchange neighborhood mechanism in a discrete bat algorithm to solve the quadratic assignment problem. Egyptian Informatics Journal, 18(3), 221-232.
Said, G. A. E. N. A., Mahmoud, A. M., & El-Horbaty, E. S. M. (2014). A comparative study of meta-heuristic algorithms for solving quadratic assignment problem. International Journal of Advanced Computer Science and Applications (IJACSA), 5(1), 1–6.
Shariff, S. R., Moin, N. H., & Omar, M. (2012). Location allocation modeling for healthcare facility planning in Malaysia. Computers & Industrial Engineering, 62(4), 1000-1010.
Şahinkoç, M., & Bilge, Ü. (2018). Facility layout problem with QAP formulation under scenario-based uncertainty. INFOR: Information Systems and Operational Research, 56(4), 406-427.
Samanta, S., Philip, D., & Chakraborty, S. (2018). Bi-objective dependent location quadratic assignment problem: Formulation and solution using a modified artificial bee colony algorithm. Computers & Industrial Engineering, 121, 8-26.
Scalia, G., Micale, R., Giallanza, A., & Marannano, G. (2019). Firefly algorithm based upon slicing structure encoding for unequal facility layout problem. International Journal of Industrial Engineering Computations, 10(3), 349-360.
Shukla, A. (2015, May). A modified bat algorithm for the quadratic assignment problem. In 2015 IEEE Congress on Evolutionary Computation (CEC) (pp. 486-490). IEEE.
Da Silva, G. C., Bahiense, L., Ochi, L. S., & Boaventura-Netto, P. O. (2012). The dynamic space allocation problem: Applying hybrid GRASP and Tabu search metaheuristics. Computers & Operations Research, 39(3), 671-677.
Syam, S. S., & Côté, M. J. (2010). A location–allocation model for service providers with application to not-for-profit health care organizations. Omega, 38(3-4), 157-166.
Tasgetiren, M. F., Pan, Q. K., Suganthan, P. N., & Dizbay, I. E. (2013, April). Metaheuristic algorithms for the quadratic assignment problem. In 2013 IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS) (pp. 131-137). IEEE.
Van Luong, T., Melab, N., & Talbi, E. G. (2010, July). Parallel hybrid evolutionary algorithms on GPU. In IEEE Congress on Evolutionary Computation (pp. 1-8). IEEE.
Xia, X., & Zhou, Y. (2018). Performance analysis of ACO on the quadratic assignment problem. Chinese Journal of Electronics, 27(1), 26-34.
Zhang, Y., Berman, O., Marcotte, P., & Verter, V. (2010). A bilevel model for preventive healthcare facility network design with congestion. IIE Transactions, 42(12), 865-880.