Abstract
This paper presents a hybrid swarm-based optimization algorithm that combines genetic algorithm (GA) and variable neighborhood search (VNS) to deal with highly-constrained nurse scheduling problems in modern hospital environments. The problem is first divided into several sub-problems by the average principle. Then a genetic algorithm is used to solve the sub-problems including a subset of constraints. Better feasible solutions are built by a hybrid genetic algorithm; they are taken as the initial solution of the variable neighborhood search procedure. The proposed algorithm can be applied to other resource allocation problems with a large number of constraints. The experiment results show that our method can produce feasible solutions.
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References
Burke, E.K., Li, J., Qu, R.: A hybrid model of integer programming and variable neighborhood search. European Journal of Operational Research 203, 439–484 (2010)
Aickelin, U., Dowsland, K.A.: Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem. Journal of Scheduling 3(3), 139–153 (2000)
Kawanaka, H., Yamamoto, K., Yoshikawa, T., Shinogi, T., Tsuruoka, S.: Genetic Algorithm with the Constraints for Nurse Scheduling Problem. Evolutionary Computation 2, 1123–1130 (2001)
Ohki, M., Morimoto, A., Miyake, K.: Nurse Scheduling by Using Cooperative GA with Efficient Mutation and Mountain-Climbing Operators. Intelligent Systems, 164–169 (2006)
Burke, E.: Variable neighborhood search for nurse rostering problems. Metaheuristics: Computer Decision-Making, 153–172 (2003)
Goodman, M.D., Dowsland, K.A., Thompson, J.M.: A grasp-knapsack hybrid for a nurse-scheduling problem. Journal of Heuristics 15, 351–379 (2009)
Gutjahr, W.J., Rauner, M.S.: An ACO algorithm for a dynamic regional nurse-scheduling problem in Austia. Computers & Operations Research 34, 642–666 (2007)
Maenhout, B., Vanhoucke, M.: An electromagnetic meta-heuristic for the nurse scheduling problem. Journal of Heuristics 13, 359–385 (2007)
Maenhout, B., Vanhoucke, M.: Comparison and hybridization of crossover operators for the nurse scheduling problem. Annals of Operations Research 159, 333–353 (2008)
Karp, R.M.: Reducibility among combinatorial problems. Complexity of Computer Computations, 85–103 (1972)
Tien, J.M., Kamiyama, A.: On manpower scheduling algorithms. Society for Industrial and Applied Mathematics 24, 275–287 (1982)
Mladenovic, N., Hansen, P.: Variable neighbourhood search. Computers and Operations Research 24, 1097–1100 (1997)
Hansen, P., Mladenovic, N.: Variable neighbourhood search: Principles and applications. European Journal of Operational Research 130, 449–467 (1999)
Gonzáles, C.G., Pérez-Brito, D.: A variable neighbourhood search for solving the linear ordering problem. In: Proceedings of the Fourth Metaheuristics International Conference (MIC), pp. 181–185 (2001)
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Zhang, Z., Hao, Z., Huang, H. (2011). Hybrid Swarm-Based Optimization Algorithm of GA & VNS for Nurse Scheduling Problem. In: Liu, B., Chai, C. (eds) Information Computing and Applications. ICICA 2011. Lecture Notes in Computer Science, vol 7030. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25255-6_48
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DOI: https://doi.org/10.1007/978-3-642-25255-6_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25254-9
Online ISBN: 978-3-642-25255-6
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