Rigorous global search: continuous problems The monograph gives a survey of interval arithmetic based methods for solving systems of equations and global optimization problems. The connection between these two themes is that zero finding is an almost unavoidable part of optimization. The interval arithmetic philosophy of selfvalidation is followed in the book as indicated by the term “rigorous” in the title. That means that for each of the two problems all solutions are to be found and enclosed in sufficiently small boxes. In addition the solutions ought to be unique in these boxes. -- The book contains standard results, new results and ones that need further development. Algorithmic and practical tools are emphasized, theoretical considerations are sporadically present. Many extensive remarks and explanations are connected with INTLIB, INTLIB 90 and INTOPT 90 which are the authors’s software and library packages for interval arithmetic and the solvers for the above mentioned problems in FORTRAN 77 resp. FORTRAN 90. par The book consists of seven chapters and a bibliography of 247 items. The first chapter (69 pages) introduces interval arithmetic, solving linear interval equations, automatic differentiation and code list generation, interval Newton method, and a short glance at the topological degree idea, which seems a bit outside the interval scope of the book. A groad chapter (42 pages) about interval software follows. Described are primarily the packages mentioned before which allow, among others, the generation of code lists and automatic differentiation. The chapter on preconditioning (32 pages) contains some of the authors own results and it provides techniques to transform linear interval equations into ones which might have tighter solution intervals. The chapter about solving nonlinear systems of equations (23 pages) features a rather practical and numerical approach in a branch and bound pattern touching many software details. The chapter on global optimization (40 pages) only admits equality constraints (within a box frame). The solution procedures are based on branch and bound, infeasibility test, interval Newton algorithm applied to the John conditions and computationally executed proofs of the existence of feasible points generalizing Hansen and Walster’s pioneering concept of 1987 (Nonlinear equations and optimization. Preprint.). The chapter about non-differentiable problems (17 pages) studies function expressions containing if-then-else connectives obtaining some new results with respect to zero search. The final chapter about intermediate values (8 pages) remains on the very surface of such a topic and contains only introductory examples of how these values can be used to reduce the overestimation.

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  1. Imbach, Rémi; Moroz, Guillaume; Pouget, Marc: A certified numerical algorithm for the topology of resultant and discriminant curves (2017)
  2. Hladík, Milan: An extension of the $\alpha\mathrmBB$-type underestimation to linear parametric Hessian matrices (2016)
  3. Schulze Darup, Moritz; Mönnigmann, Martin: Improved automatic computation of Hessian matrix spectral bounds (2016)
  4. Baidya, Abhijit; Bera, Uttam Kumar; Maiti, Manoranjan: Interval oriented entropy based multi-item solid transportation problem with budget and breakability (2015)
  5. Enszer, Joshua A.; Andrei Măceş, D.; Stadtherr, Mark A.: Probability bounds analysis for nonlinear population ecology models (2015)
  6. Hladík, Milan: On the efficient Gerschgorin inclusion usage in the global optimization $\alpha$BB method (2015)
  7. Kearfott, Ralph Baker: Some observations on exclusion regions in branch and bound algorithms (2015)
  8. Kubica, Bartłomiej Jacek: Presentation of a highly tuned multithreaded interval solver for underdetermined and well-determined nonlinear systems (2015)
  9. Ninin, Jordan; Messine, Frédéric; Hansen, Pierre: A reliable affine relaxation method for global optimization (2015)
  10. Scott, Joseph K.; Barton, Paul I.: Reachability analysis and deterministic global optimization of DAE models (2015)
  11. Semenov, V.Yu.: A method to find all the roots of the system of nonlinear algebraic equations based on the Krawczyk operator (2015)
  12. Araya, Ignacio; Trombettoni, Gilles; Neveu, Bertrand; Chabert, Gilles: Upper bounding in inner regions for global optimization under inequality constraints (2014)
  13. Gasilov, N.A.; Fatullayev, A.G.; Amrahov, Ş.E.; Khastan, A.: A new approach to fuzzy initial value problem (2014)
  14. Gasilov, Nizami; Amrahov, Şahin Emrah; Fatullayev, Afet Golayoglu: Solution of linear differential equations with fuzzy boundary values (2014)
  15. Houska, Boris; Chachuat, Beno^ıt: Branch-and-lift algorithm for deterministic global optimization in nonlinear optimal control (2014)
  16. Karmakar, Samiran; Bhunia, Asoke Kumar: An alternative optimization technique for interval objective constrained optimization problems via multiobjective programming (2014)
  17. Kearfott, Ralph Baker: On rigorous upper bounds to a global optimum (2014)
  18. Schichl, Hermann; Markót, Mihály Csaba; Neumaier, Arnold: Exclusion regions for optimization problems (2014)
  19. Allahviranloo, T.; Salahshour, S.; Homayoun-Nejad, M.; Baleanu, D.: General solutions of fully fuzzy linear systems (2013)
  20. Bedregal, Benjamín; Santiago, Regivan: Some continuity notions for interval functions and representation (2013)

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