Memes, self-generation and nurse rostering

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3867 LNCS, Issue , 2006, Pages 85-104

  Özcan, Ender ^a  

^a YEDITEPE UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINT THEORY; GENETIC ALGORITHMS; HEURISTIC ALGORITHMS; NURSING; PERSONNEL; PROBLEM SOLVING; SCHEDULING;

MEMETIC ALGORITHMS; NURSE ROSTERING;

RESOURCE ALLOCATION;

EID: 38549083110     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Conference Paper

References (54)

1. Ackley, D.: An empirical study of bit vector function optimization. In: Davis, L. (ed.) Genetic Algorithms and Simulated Annealing, pp. 170-215. Pitman, London (1987)
2. Ahmad, J., Yamamoto, M., Ohuchi, A.: Evolutionary algorithms for nurse scheduling problem. In: Proceedings of the IEEE Congress on Evolutionary Computation, pp. 196-203 (2000)
3. Aickelin, U., Bull, L.: On the application of hierarchical coevolutionary genetic algorithms: recombination and evaluation partners. Journal of Applied Systems Studies 4, 2-17 (2003)
4. Aickelin, U., Dowsland, K.: An indirect genetic algorithm for a nurse scheduling problem. Computers and Operations Research 31, 761-778 (2003)
5. Alkan, A., Ozcan, E.: Memetic algorithms for timetabling. In: Proceedings of the IEEE Congress on Evolutionary Computation, pp. 1796-1802 (2003)
6. Berrada, I., Ferland, J., Michelon, P.: A multi-objective approach to nurse scheduling with both hard and soft constraints. Socio-Economic Planning Science 30, 183-193 (1996)
7. Burke, E.K., Cowling, P.I., De Causmaecker, P., Vanden Berghe, G.: A memetic approach to the nurse rostering problem. Applied Intelligence 15, 199-214 (2001)
8. Burke, E.K., De Causmaecker, P., Petrovic, S., Vanden Berghe, G.: Variable neighbourhood search for nurse rostering problems. In: Resende, M.G.C., de Sousa, J.P. (eds.) Metaheuristics: Computer Decision-Making, ch. 7, pp. 153-172. Kluwer, Dordrecht (2003)
9. Burke, E.K., De Causmaecker, P., Vanden Berghe, G.: A hybrid tabu search algorithm for the nurse rostering problem. In: McKay, B., Yao, X., Newton, C.S., Kim, J.-H., Furuhashi, T. (eds.) SEAL 1998. LNCS (LNAI), vol. 1585, pp. 187-194. Springer, Heidelberg (1999)
10. Burke, E.K., De Causmaecker, P., Vanden Berghe, G., Van Landeghem, H.: The state of the art of nurse rostering. Journal of Scheduling 7, 441-499 (2004)
11. Burke, E.K., Kendall, G., Newall, J., Hart, E., Ross, P., Schulenburg, S.: Hyperheuristics: an emerging direction in modern search technology. In: Glover, F., Kochenberger, G. (eds.) Handbook of Metaheuristics, pp. 457-474. Kluwer, Dordrecht (2003)
12. Burke, E.K., Kendall, G., Soubeiga, E.: A tabu-search hyperheuristic for time-tabling and rostering. Journal of Heuristics 9, 451-470 (2003)
13. Chun, A.H.W., Chan, S.H.C., Lam, G.P.S., Tsang, F.M.F., Wong, J., Yeung, D.W.M.: Nurse rostering at the Hospital Authority of Hong Kong. In: Proceedings of the 17th National Conference on AAAI and 12th Conference on IAAI, pp. 951-956 (2000)
14. Cowling, P., Kendall, G., Soubeiga, E.: A hyper-heuristic approach to scheduling a sales summit. In: Burke, E., Erben, W. (eds.) PATAT 2000. LNCS, vol. 2079, pp. 176-190. Springer, Heidelberg (2001)
15. Davis, L.: The Handbook of Genetic Algorithms. Van Nostrand Reinhold, New York (1991)
16. Davis, L.: Bit climbing, representational bias, and test suite design. In: Proceedings of the 4th International Conference on Genetic Algorithms, pp. 18-23 (1991)
17. De Jong, K.: An analysis of the behaviour of a class of genetic adaptive systems. Ph.D. Thesis, University of Michigan, Ann Arbor, MI (1975)
18. Dowsland, K.: Nurse scheduling with tabu search and strategic oscillation. European Journal of Operations Research 106, 393-407 (1998)
19. Duenas, A., Mort, N., Reeves, C., Petrovic, D.: Handling preferences using genetic algorithms for the nurse scheduling problem. In: MISTA 2003. Proceedings of the 1st Multidisciplinary International Conference on Scheduling: Theory and Applications, Nottingham, vol. 1, pp. 180-196 (August 2003)
20. Easom, E.E.: A survey of global optimization techniques. M.Eng. Thesis, University of Louisville, KY (1990)
21. Even, S., Itai, A., Shamir, A.: On the complexity of timetable and multicommodity flow problems. SIAM Journal of Computing 5, 691-703 (1976)
22. Fang, H.L.: Genetic algorithms in timetabling and scheduling. Ph.D. Thesis, Department of Artificial Intelligence, University of Edinburgh, Scotland (1994)
23. Gendreau, M., Buzon, I., Lapierre, S., Sadr, J., Soriano, P.: A tabu search heuristic to generate shift schedules. In: MISTA 2003. Proceedings of the 1st Multidisciplinary International Conference on Scheduling: Theory and Applications, Nottingham, vol. 2, pp. 526-528 (August 2003)
24. Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading, MA (1989)
25. Goldberg, D.E.: Genetic algorithms and Walsh functions: part I, a gentle introduction. Complex Systems 3, 129-152 (1989)
26. Goldberg, D.E.: Genetic algorithms and Walsh functions: part II, deception and its analysis. Complex Systems 3, 153-171 (1989)
27. Griewangk, A.O.: Generalized descent of global optimization. Journal of Optimization Theory and Applications 34, 11-39 (1981)
28. Holland, J.H.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, MI (1975)
29. Han, L., Kendall, G.: Application of genetic algorithm based hyper-heuristic to personnel scheduling problems. In: Kendall, G., Burke, E.K., Petrovic, S., Gendreau, M. (eds.) MISTA 2003. Proceedings of the 1st Multidisciplinary International Conference on Scheduling: Theory and Applications, Nottingham, August 2003, pp. 528-537. Springer, Berlin (2005)
30. Kawanaka, H., Yamamoto, K., Yoshikawa, T., Shinogi, T., Tsuruoka, S.: Genetic algorithms with the constraints for nurse scheduling problem. In: Proceedings of IEEE Congress on Evolutionary Computation, CEC, Seoul, pp. 1123-1130 (2001)
31. Krasnogor, N.: Studies on the theory and design space of memetic algorithms. Ph.D. Thesis, University of the West of England, Bristol, UK (2002)
32. Krasnogor, N., Smith, J.E.: Multimeme algorithms for the structure prediction and structure comparison of proteins. In: GECCO 2002. Proceedings of the Bird of a Feather Workshops, pp. 42-44 (2002)
33. Krasnogor, N., Smith, J.E.: Emergence of profitable search strategies based on a simple inheritance mechanism. In: GECCO 2001. Proceedings of the Genetic and Evolutionary Computation Conference, pp. 432-439 (2001)
34. Krasnogor, N., Smith, J.E.: A memetic algorithm with self-adaptive local search: TSP as a case study. In: GECCO 2000. Proceedings of the Genetic and Evolutionary Computation Conference, pp. 987-994 (2000)
35. Leighton, F.T.: A graph coloring algorithm for large scheduling problems. Journal of Research of the National Bureau of Standards 84, 489 (1979)
36. Li, H., Lim, A., Rodrigues, B.: A hybrid AI approach for nurse rostering problem. In: Proceedings of the 2003 ACM Symposium on Applied Computing, pp. 730-735 (2003)
37. Mitchell, M., Forrest, S.: Fitness landscapes: royal road functions. In: Baeck, T., Fogel, D., Michalewicz, Z. (eds.) Handbook of Evolutionary Computation, Institute of Physics Publishing, Bristol, and Oxford University Press, Oxford (1997)
38. Moscato, P., Norman, M.G.: A memetic approach for the traveling salesman problem implementation of a computational ecology for combinatorial optimization on message-passing systems. In: Valero, M., Onate, E., Jane, M., Larriba, J.L., Suarez, B. (eds.) Parallel Computing and Transputer Applications, pp. 177-186. IOS Press, Amsterdam (1992)
39. Ning, Z., Ong, Y.S., Wong, K.W., Lim, M.H.: Choice of memes in memetic algorithm. In: Proceedings of the 2nd International Conference on Computational Intelligence, Robotics and Autonomous Systems (2003)
40. Ong, Y.S., Keane, A.J.: Meta-Lamarckian learning in memetic algorithms. IEEE Transactions on Evolutionary Computation 8, 99-110 (2004)
41. Özcan, E.: Memetic Algorithms for Nurse Rostering. In: Yolum, p., Güngör, T., Gürgen, F., Özturan, C. (eds.) ISCIS 2005. LNCS, vol. 3733, pp. 482-492. Springer, Heidelberg (2005)
42. Özcan, E.: Towards an XML based standard for timetabling problems: TTML. In: Kendall, G., Burke, E.K., Petrovic, S., Gendreau, M. (eds.) MISTA 2003. Proceedings of the 1st Multidisciplinary International Conference on Scheduling: Theory and Applications, Nottingham, p. 163. Springer, Berlin (August 2005)
43. Özcan, E., Bilgin, B., Korkmaz, E.E.: Hill climbers and mutational heuristics in hyperheuristics. In: Runarsson, T.P., Beyer, H.-G., Burke, E., Merelo-Guervós, J.J., Whitley, L.D., Yao, X. (eds.) Parallel Problem Solving from Nature - PPSN IX. LNCS, vol. 4193, pp. 202-211. Springer, Heidelberg (2006)
44. Özcan, E., Ersoy, E.: Final exam scheduler - FES. In: Proceedings of the 2005 IEEE Congress on Evolutionary Computation, vol. 2, pp. 1356-1363 (2005)
45. Özcan, E., Onbasioglu, E.: Memetic algorithms for parallel code optimization. International Journal of Parallel Programming 35, 33-61 (2007)
46. Radcliffe, N.J., Surry, P.D.: Formal memetic algorithms. In: Fogarty, T.C. (ed.) Evolutionary Computing. LNCS, vol. 865, pp. 1-16. Springer, Heidelberg (1994)
47. Rastrigin, L.A.: Extremal Control Systems, Theoretical Foundations of Engineering Cybernetics Series, Nauka, Moscow (1974)
48. Ross, P., Corne, D., Fang, H.-L.: Improving evolutionary timetabling with delta evaluation and directed mutation. In: Davidor, Y., Männer, R., Schwefel, H.-P. (eds.) Parallel Problem Solving from Nature - PPSN III. LNCS, vol. 866, pp. 556-565. Springer, Heidelberg (1994)
49. Ross, P., Corne, D., Fang, H.-L.: Fast practical evolutionary timetabling. In: Proceedings of the AISB Workshop on Evolutionary Computation, pp. 250-263 (1994)
50. Schwefel, H.-P.: Numerical Optimization of Computer Models. Wiley, Chichester (1981)
51. Schwefel, H.-P.: Evolution and Optimum Seeking. Wiley, New York (1995)
52. Smith, J., Fogarty, T.C.: Operator and parameter adaptation in genetic algorithms. Soft Computing 1, 81-87 (1997)
53. Tasoulis, D., Pavlidis, N., Plagianakos, V., Vrahatis, M.: Parallel differential evolution. In: Proceedings of the 2004 IEEE Congress on Evolutionary Computation, pp. 2023-2029. IEEE Computer Society Press, Los Alamitos (2004)
54. Whitley, D.: Fundamental principles of deception in genetic search. In: Rawlins, G.J.E. (ed.) Foundations of Genetic Algorithms, Morgan Kaufmann, San Mateo, CA (1991)