Now showing items 1-2 of 2

  • Multi-objective optimisation of cancer chemotherapy using evolutionary algorithms. 

    Petrovski, Andrei; McCall, John (Springer http://dx.doi.org/10.1007/3-540-44719-9, 2001)
    PETROVSKI, A. and MCCALL, J., 2001. Multi-objective optimisation of cancer chemotherapy using evolutionary algorithms. In: ZITZLEF, E., DEB, K., THIELE, L., COELLO, C. and CORNE, D. Evolutionary Multi-criterion Optimization : First International Conference, EMO 2001, Zurich, Switzerland, March 2001 : Proceedings. Berlin: Springer. pp. 531-545.
    The main objectives of cancer treatment in general, and of cancer chemotherapy in particular, are to eradicate the tumour and to prolong the patient survival time. Traditionally, treatments are optimised with only ...
  • Problem dependent metaheuristic performance in Bayesian network structure learning. 

    Wu, Yanghui (Robert Gordon University School of Computing Science and Digital Media, 2012-09)
    Bayesian network (BN) structure learning from data has been an active research area in the machine learning field in recent decades. Much of the research has considered BN structure learning as an optimization problem. ...