Harmony Search with Greedy Shuffle for Nurse Rostering
2012, International Journal of Natural Computing Research
Abstract
In this paper, a hybridization of Harmony Search Algorithm (HSA) with a greedy shuffle move is proposed for Nurse Rostering Problem (NRP). NRP is a combinatorial optimization problem that is tackled by assigning a set of nurses with different skills and contracts to different types of shifts, over a pre-determined scheduling period. HSA is a population-based method which mimics the improvisation process that has been successfully applied for a wide range of optimization problems. The performance of HSA is enhanced by hybridizing it with a greedy shuffle move. The proposed method is evaluated using a dataset defined in first International Nurse Rostering Competition (INRC2010). The hybrid HSA obtained the best results of the comparative methods in four datasets.
References (47)
- Al-Betar, M. A., Doush, I. A., Khader, A. T., & Awadallah, M. A. (2012). Novel selection schemes for harmony search. Applied Mathematics and Computation, 218(10), 6095- 6117.
- Al-Betar, M. A., & Khader, A. (2009). A hybrid harmony search for university course timetabling. Paper presented at the Proceedings of the 4nd Multidisciplinary Conference on Scheduling: Theory and Applications (MISTA 2009), Dublin, Ireland, August, 157- 179.
- Al-Betar, M. A., Khader, A. T., & Nadi, F. (2010). Selection mechanisms in memory consideration for examination timetabling with harmony search. Paper presented at the Proceedings of the 12th annual conference on Genetic and evolutionary computation, 1203-1210.
- Al-Betar, M. A., Khader, A. T., & Thomas, J. J. (2010). A Combination of Metaheuristic Components based on Harmony Search for The Uncapacitated Examination Timetabling. Paper presented at the 8th International Conference on the Practice and Theory of Automated Timetabling (PATAT 2010). , Belfast, Northern Ireland, August, 57-80.
- Al-Betar, M. A., Khader, A. T., & Zaman, M. (2012). University course timetabling using a hybrid harmony search metaheuristic algorithm. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews. DOI: 10.1109/TSMCC.2011.2174356., 99, 1-18.
- Alatas, B. (2010). Chaotic harmony search algorithms. Applied Mathematics and Computation, 216(9), 2687-2699.
- Awadallah, M., Khader, A., Al-Betar, M., & Bolaji, A. (2011). Nurse Rostering Using Modified Harmony Search Algorithm. Swarm, Evolutionary, and Memetic Computing, 27-37.
- Awadallah, M. A., Khader, A. T., Al-Betar, M. A., & Bolaji, A. L. (2011). Nurse Scheduling Using Harmony Search. Paper presented at the Bio-Inspired Computing: Theories and Applications (BIC-TA), 2011 Sixth International Conference, 58-63.
- Bellanti, F., Carello, G., Della Croce, F., & Tadei, R. (2004). A greedy-based neighborhood search approach to a nurse rostering problem. European Journal of Operational Research, 153(1), 28-40.
- Bilgin, B., De Causmaecker, P., Rossie, B., & Vanden Berghe, G. (2011). Local search neighbourhoods for dealing with a novel nurse rostering model. Annals of Operations Research, 1-25.
- Bilgin, B., Demeester, P., Misir, M., Vancroonenburg, W., Vanden Berghe, G., & Wauters, T. (2010). A hyper-heuristic combined with a greedy shuffle approach to the nurse rostering competition: INRC2010 (http://www.kuleuven-kortrijk.be/nrpcompetition).
- Blum, C., & Roli, A. (2003). Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Computing Surveys (CSUR), 35(3), 268-308.
- Brusco, M. J., & Jacobs, L. W. (1995). Cost analysis of alternative formulations for personnel scheduling in continuously operating organizations. European journal of operational research, 86(2), 249-261.
- Burke, E. K., Cowling, P., De Causmaecker, P., & Berghe, G. V. (2001). A memetic approach to the nurse rostering problem. Applied intelligence, 15(3), 199-214.
- Burke, E. K., & Curtois, T. (2010). An ejection chain method and a branch and price algorithm applied to the instances of the first international nurse rostering competition: INRC2010 (http://www.kuleuven-kortrijk.be/nrpcompetition).
- Burke, E. K., Curtois, T., Post, G., Qu, R., & Veltman, B. (2008). A hybrid heuristic ordering and variable neighbourhood search for the nurse rostering problem. European journal of operational research, 188(2), 330-341.
- Burke, E. K., Curtois, T., Qu, R., & Berghe, G. V. (2009). A scatter search methodology for the nurse rostering problem. Journal of the Operational Research Society, 61(11), 1667- 1679.
- Burke, E. K., De Causmaecker, P., Berghe, G. V., & Van Landeghem, H. (2004). The state of the art of nurse rostering. Journal of scheduling, 7(6), 441-499.
- Burke, E. K., De Causmaecker, P., & Vanden Berghe, G. (1999). A hybrid tabu search algorithm for the nurse rostering problem. Simulated evolution and learning, 187-194.
- Cai, X., & Li, K. N. (2000). A genetic algorithm for scheduling staff of mixed skills under multi- criteria. European journal of operational research, 125(2), 359-369.
- Cheang, B., Li, H., Lim, A., & Rodrigues, B. (2003). Nurse rostering problems--a bibliographic survey. European journal of operational research, 151(3), 447-460.
- Dowsland, K. A. (1998). Nurse scheduling with tabu search and strategic oscillation. European journal of operational research, 106(2-3), 393-407.
- Fesanghary, M., Mahdavi, M., Minary-Jolandan, M., & Alizadeh, Y. (2008). Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems. Computer methods in applied mechanics and engineering, 197(33-40), 3080-3091.
- Forsati, R., Haghighat, A. T., & Mahdavi, M. (2008). Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing. Computer Communications, 31(10), 2505-2519.
- Geem, Z. W. (2005). Harmony search in water pump switching problem. Advances in Natural Computation, 445-445.
- Geem, Z. W. (2008). Harmony search applications in industry. Soft Computing Applications in Industry, 117-134.
- Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A new heuristic optimization algorithm: harmony search. Simulation, 76(2), 60-68.
- Geem, Z. W., Lee, K. S., & Park, Y. (2005). Application of harmony search to vehicle routing. American Journal of Applied Sciences, 2(12), 1552-1557.
- Geem, Z. W., & Sim, K. B. (2010). Parameter-setting-free harmony search algorithm. Applied Mathematics and Computation, 217(8), 3881-3889.
- Gutjahr, W. J., & Rauner, M. S. (2007). An ACO algorithm for a dynamic regional nurse- scheduling problem in Austria. Computers & Operations Research, 34(3), 642-666.
- Kaveh, A., & Talatahari, S. (2009). Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures. Computers & Structures, 87(5-6), 267-283.
- Lee, K. S., & Geem, Z. W. (2005). A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice. Computer methods in applied mechanics and engineering, 194(36-38), 3902-3933.
- Lee, K. S., Geem, Z. W., Lee, S., & Bae, K. (2005). The harmony search heuristic algorithm for discrete structural optimization. Engineering Optimization, 37(7), 663-684.
- Lu, Z., & Hao, J.-K. (2010). Adaptive local search for the first international nurse rostering competition: INRC2010 (http://www.kuleuven-kortrijk.be/nrpcompetition).
- Maenhout, B., & Vanhoucke, M. (2007). An electromagnetic meta-heuristic for the nurse scheduling problem. Journal of Heuristics, 13(4), 359-385.
- Mahdavi, M., Fesanghary, M., & Damangir, E. (2007). An improved harmony search algorithm for solving optimization problems. Applied Mathematics and Computation, 188(2), 1567- 1579.
- Millar, H. H., & Kiragu, M. (1998). Cyclic and non-cyclic scheduling of 12 h shift nurses by network programming. European journal of operational research, 104(3), 582-592.
- Nonobe, K. (2010). INRC2010: An Approach Using a General Constraint Optimization Solver: INRC2010 (http://www.kuleuven-kortrijk.be/nrpcompetition).
- Özcan, E. (2005). Memetic algorithms for nurse rostering. Computer and Information Sciences- ISCIS 2005, 482-492.
- Tsai, C. C., & Li, S. H. A. (2009). A two-stage modeling with genetic algorithms for the nurse scheduling problem. Expert Systems with Applications, 36(5), 9506-9512.
- Valouxis, C., Gogos, C., Goulas, G., Alefragis, P., & Housos, E. (2010). A systematic two phase approach for the Nurse Rostering problem: INRC2010 (http://www.kuleuven- kortrijk.be/nrpcompetition).
- Wren, A. (1996). Scheduling, timetabling and rostering -A special relationship? Practice and Theory of Automated Timetabling, 46-75.
- The set day-off preferences are represented as (Nurse ID, day, weight). In this dataset, there exist 490 preferences as a day-off for all nurses. i. 35, 2010-01-02, 1; ii. 35, 2010-01-11, 1; iii. 35, 2010-01-21, 1; iv. 35, 2010-01-16, 1;
- ……………
- The set day-on preferences are represented as (Nurse ID, day, weight). In this dataset, no day-on preferences for all nurses.
- The set shift-off preferences are represented as (Nurse ID, day, shift ID, weight). In this dataset, there exist 245 preferences as a shift-off for all nurses. i. 35, 2010-01-09, L, 1; ii. 35, 2010-01-05, D, 1; iii. 35, 2010-01-08, L, 1; iv. 35, 2010-01-27, L, 1;
- The set shift-on preferences are represented as (Nurse ID, day, shift ID, weight). In this dataset, no shift-on preferences for all nurses.