Applying hybrid multiobjective evolutionary algorithms to the sailor assignment problem

Studies in Computational Intelligence

Volumn 66, Issue , 2007, Pages 269-301

  Garrett, Deon ^a   Dasgupta, Dipankar ^a   Vannucci, Joseph ^a   Simien, James ^b  

^a UNIVERSITY OF MEMPHIS   (United States)

^b Studies   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 34447502045     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-72377-6_12     Document Type: Article

References (30)

1. A. Ali, J. Kennington, and T. Liang. Assignment with en route training of navy personnel. Naval Research Logistics, 40:581-592, 1993.
2. T. Blanco and R. Hillery. A sea story: Implementing the navy's personnel assignment system. Operations Research, 42(5):814-822, 1994.
3. P. Bosman and E. de Jong. Exploiting gradient information in numerical multiobjective evolutionary optimization. In Una May O'Reilly, editor, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '05), 2005.
4. M. Brown and R. E. Smith. Effective use of directional information in multiobjective evolutionary computation. In E. Cantu-Paz et al., editors, Proceedings of the 2003 Genetic and Evolutionary Computation Conference (GECCO '03), pages 778-789. Springer-Verlag, 2003.
5. Paola Cappanera and Giorgio Gallo. A multicommodity flow approach to the crew rostering problem. Operations Research, 52(4):583-596, July-August 2004.
6. Eranda Cela. The Quadratic Assignment Problem: Theory and Applications. Kluwer Academic Publishers, 1998.
7. D. Cvetković and I. Parmee. Use of preferences for ga-based multi-objective optimization. In W. Banzhaf et al., editors, Proceedings of the 1999 Genetic and Evolutionary Computation Conference (GECCO '99), pages 1504-1509. Morgan-Kaufmann, 1999.
8. Kalyanmoy Deb. Multi-Objective Optimization using Evolutionary Algorithms. John Wiley & Sons, 2001.
9. Kalyanmoy Deb, A. Pratap, Sameer Agarwal, and T. Meyarivan. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6:182-197, 2002.
10. N. Drechsler, R. Drechsler, and B. Becker. Multi-objective optimization based on relation favour. In E. Zitzler et al., editors, First International Conference on Evolutionary Multi-Criterion Optimization pages 154-166. Springer-Verlag, 2001.
11. L. Eshelman. The CHC adaptive search algorithm. In Foundations of Genetic Algorithms I, pages 265-283. Morgan Kaufmann, 1991.
12. Harald Feltl and Günther Raidl. An improved hybrid genetic algorithm for the generalized assignment problem. In 2004 ACM Symposium on Applied Computing, pages 990-995, 2004.
13. P. Fleming, R. Purshouse, and R. Lygoe. Many-objective optimization: An engineering design perspective. In C. Coello-Coello et al., editors, Third International Conference on Evolutionary Multi-Criterion Optimization, pages 14-32. Springer, 2005.
14. Charles Fleurent and Jaques Ferland. Genetic hybrids for the quadratic assignment problem. DIMACS Series in Discrete Mathematics and Theoretical Computer Science, 16, Quadratic Assignment and Related Problems:173-187, 1994.
15. D. Gale and L. S. Shapley. College admissions and the stability of marriage. The American Mathematical Monthly, 69(1):9-15, 1962.
16. J. Deon Garrett, Joseph Vannucci, Rodrigo Silva, Dipankar Dasgupta, and James Simien. Genetic algorithms for the sailor assignment problem. In Proceedings of the 2005 Genetic and Evolutionary Computation Conference (GECCO '05), 2005.
17. Allen Holder. Navy personnel planning and the optimal partition. Operations Research, 53(1):77-89, January-February 2005.
18. H. Ishibuchi and T. Murata. Multi-objective genetic local search algorithm. In T. Fukuda and T. Furuhashi, editors, Proceedings of the 1996 International Conference on Evolutionary Computation, pages 119-124, 1996.
19. A. Jaszkiewicz. Genetic local search for multiple objective combinatorial optimization. Technical Report RA-014/98, Institute of Computing Science, Poznan University of Technology, December 1998.
20. Hamid Kharraziha, Marek Ozana, and Sami Spjuth. Large scale crew rostering. Technical Report CRTR-0305, Carmen Systems, September 2003.
21. J. D. Knowles and D. Corne. Memetic algorithms for multiobjective optimization: Issues, methods and prospects. In N. Krasnogor, J. E. Smith, and W. E. Hart, editors, Recent Advances in Memetic Algorithms Springer, 2004.
22. Joshua D. Knowles and David Corne. M-PAES: A memetic algorithm for multiobjective optimization. In Proceedings of the 2000 Congress on Evolutionary Computation (CEC-2000), pages 325-332. IEEE Press, 2000.
23. Mark W. Lewis, Karen R. Lewis, and Barbara J. White. Guided design search in the interval-bounded sailor assignment problem. Technical Report HCES-04- 04, Hearin Center for Enterprise Science, The University of Mississippi, April 2004.
24. Lee McCauley and Stan Franklin. A large-scale multi-agent system for navy personnel distribution. Connection Science, 14(4):371-385, December 2002.
25. Peter Merz and Bernd Freisleben. A genetic local search approach to the quadratic assignment problem. In Proceedings of the Seventh International Conference on Genetic Algorithms, 1997.
26. P. Moscato. Memetic algorithms: A short introduction. In D. Corne, F. Glover, and M. Dorigo, editors, New Ideas in Optimization, pages 219-234. McGraw- Hill, 1999.
27. Walid El Moudani, Carlos Alberto Nunes Cosenza, Marc de Coligny, and Félix Mora-Camino. A bi-criterion approach for the airlines crew rostering problem. In Eckart Zitzler, Kalyanmoy Deb, Lothar Thiele, Carlos A. Coello-Coello, and David Corne, editors, First International Conference on Evolutionary Multi- Criterion Optimization pages 486-500. Springer-Verlag, 2001.
28. N. Radcliffe. Forma analysis and random respectful recombination. In R.K. Belew and L.B. Booker, editors, Proceedings of the Fourth International Conference on Genetic Algorithms. Morgan Kaufman, 1991.
29. J. D. Schaffer. Multi-objective optimization with vector evaluated genetic algorithms. In J. J. Grefenstette, editor, Proceedings of an International Conference on Genetic Algorithms and Their Applications pages 93-100, 1985.
30. Eckart Zitzler, Marco Laumanns, and Lothar Thiele. SPEA2: Improving the strength pareto evolutionary algorithm. Technical Report 103, Computer Engineering and Networks Laboratory (TIK), Swiss Federal Institute of Technology (ETH), Zurich, Switzerland, May 2001.