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Enhanced hospital resource management using anticipatory policies in online dynamic multi-objective optimization

Published:07 July 2010Publication History

ABSTRACT

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References

  1. P. A. N. Bosman and H. La Poutré. Learning and e anticipation in online dynamic optimization with evolutionary algorithms: The stochastic case. In D. Thierens et al., editors, Proc. of the Genetic and Evolutionary Comp. Conf. - GECCO-2007, pages 1165--1172, 2007. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. P. A. N. Bosman and D. Thierens. Adaptive variance scaling in continuous multi-objective estimation-of-distribution algorithms. In D. Thierens et al., editors, Proceedings of the Genetic and Evolutionary Computation Conference - GECCO-2007, pages 500--507, 2007. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. J. Branke and D. Mattfeld. Anticipation and flexibility in dynamic scheduling. International Journal of Production Research, 43(15):3103--3129, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  4. L. T. Bui, J. Branke, and H. Abbass. Multiobjective optimization for dynamic environments. In Congress on Evol. Computation, pages 2349--2356, 2005. IEEE Press.Google ScholarGoogle Scholar
  5. A. K. Hutzschenreuter, P. A. N. Bosman, I. Blonk-Altena, J. van Aarle, and H. La Poutré. Agent-based patient e admission scheduling in hospitals. In L. Padgham et al., editors, Autonomous Agents and Multiagent Systems - AAMAS--2008, pages 45--54. IFAAMAS, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library

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