An introduction to possibilistic optimization: theory, solution methods, comparisons and an application to radiation Therapy of Tumors

Description:  Optimization in the presence of various types of uncertainty in the values of parameters and ambiguity in the constraining relationships is introduced. Solution algorithms are discussed and one example is used to illustrate the similarities and differences among deterministic, stochastic and possibilistic linear programming. Extensions to the general mathematical programming problem is indicated. An application of possibilistic linear programming to radiation therapy of tumors is outlined. NOTE: Given the extent of the topics of this talk, a sketch of the most fundamental issues is presented. I will make some copies of the overheads available. Area(s): Date:  2000-10-04 Start Time:   14:00 Speaker:  Weldon A. Lodwick (Fulbright Fellow, University of Coimbra and University of Colorado) Place:  Room 2.5 Research Groups: -Numerical Analysis and Optimization See more:   <Main>