00870nam0-2200253 --450 991059410080332120221004155705.020221004d1909----kmuy0itay5050 baitaIT 001yy<<La >>proposta della sterilizzazione dei più anormali quale misura profilattica sociale contro la degenerazioneA. ZuccarelliNapoliTip. N. Jovene e C.190917 p.24 cmEstratto dalla rivista: L'anomalo 1909.30123itaZuccarelli,Angelo80020ITUNINAREICATUNIMARCBK9910594100803321Busta 28(1) 9S.I.FGBCFGBCProposta della sterilizzazione dei più anormali quale misura profilattica sociale contro la degenerazione2916313UNINA02834nam 2200493 450 99646655140331620210312134500.03-030-61821-810.1007/978-3-030-61821-6(CKB)4100000011728409(DE-He213)978-3-030-61821-6(MiAaPQ)EBC6461891(PPN)253254256(EXLCZ)99410000001172840920210312d2021 uy 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierAdvancing parametric optimization on multiparametric linear complementarity problems with parameters in general locations /Nathan Adelgren1st ed. 2021.Cham, Switzerland :Springer,[2021]©20211 online resource (XII, 113 p. 8 illus., 7 illus. in color.) SpringerBriefs in Optimization,2190-83543-030-61820-X Includes bibliographical references.1. Introduction -- 2. Background on mpLCP -- 3. Algebraic Properties of Invariancy Regions -- 4. Phase 2: Partitioning the Parameter Space -- 5. Phase 1: Determining an Initial Feasible Solution -- 6. Further Considerations -- 7. Assessment of Performance -- 8. Conclusion -- Appendix A. Tableaux for Example 2.1 -- Appendix B. Tableaux for Example 2.2 -- References.The theory presented in this work merges many concepts from mathematical optimization and real algebraic geometry. When unknown or uncertain data in an optimization problem is replaced with parameters, one obtains a multi-parametric optimization problem whose optimal solution comes in the form of a function of the parameters.The theory and methodology presented in this work allows one to solve both Linear Programs and convex Quadratic Programs containing parameters in any location within the problem data as well as multi-objective optimization problems with any number of convex quadratic or linear objectives and linear constraints. Applications of these classes of problems are extremely widespread, ranging from business and economics to chemical and environmental engineering. Prior to this work, no solution procedure existed for these general classes of problems except for the recently proposed algorithms.SpringerBriefs in Optimization,2190-8354Mathematical optimizationGeometry, AlgebraicMathematical optimization.Geometry, Algebraic.016.5192Adelgren Nathan1221184MiAaPQMiAaPQMiAaPQBOOK996466551403316Advancing parametric optimization2831544UNISA