Optimization Toolbox

Optimization Toolbox Product Description: Solve linear, quadratic, integer, and nonlinear optimization problems. Optimization Toolbox™ provides functions for finding parameters that minimize or maximize objectives while satisfying constraints. The toolbox includes solvers for linear programming, mixed-integer linear programming, quadratic programming, nonlinear optimization, and nonlinear least squares. You can use these solvers to find optimal solutions to continuous and discrete problems, perform tradeoff analyses, and incorporate optimization methods into algorithms and applications.

References in zbMATH (referenced in 277 articles )

Showing results 1 to 20 of 277.
Sorted by year (citations)

1 2 3 ... 12 13 14 next

  1. Audoux, Yohann; Montemurro, Marco; Pailhès, Jérôme: Non-uniform rational basis spline hyper-surfaces for metamodelling (2020)
  2. Chen, Yuan; Voskov, Denis: Optimization of (\mathrmCO_2) injection using multi-scale reconstruction of composition transport (2020)
  3. Cocchi, Guido; Levato, Tommaso; Liuzzi, Giampaolo; Sciandrone, Marco: A concave optimization-based approach for sparse multiobjective programming (2020)
  4. Floryan, Daniel; Rowley, Clarence W.: Distributed flexibility in inertial swimmers (2020)
  5. Gehlot, Hemant; Honnappa, Harsha; Ukkusuri, Satish V.: An optimal control approach to day-to-day congestion pricing for stochastic transportation networks (2020)
  6. Pantha, Buddhi; Day, Judy; Lenhart, Suzanne: Investigating the effects of intervention strategies in a spatio-temporal anthrax model (2020)
  7. Ran, Chunjiang; Yang, Haitian: An efficient numerical method to solve 2-D interval bi-modular problems via orthogonal polynomial expansion (2020)
  8. Xiao, Shiguo; Xia, Pan: Variational calculus method for passive earth pressure on rigid retaining walls with strip surcharge on backfills (2020)
  9. Brust, Johannes J.; Marcia, Roummel F.; Petra, Cosmin G.: Large-scale quasi-Newton trust-region methods with low-dimensional linear equality constraints (2019)
  10. Di Mauro, G.; Spiller, D.; Bevilacqua, R.; D’Amico, S.: Spacecraft formation flying reconfiguration with extended and impulsive maneuvers (2019)
  11. Gratton, S.; Royer, C. W.; Vicente, L. N.; Zhang, Z.: Direct search based on probabilistic feasible descent for bound and linearly constrained problems (2019)
  12. Huntul, M. J.; Lesnic, D.: Determination of a time-dependent free boundary in a two-dimensional parabolic problem (2019)
  13. Ji, Hangjie; Li, Longfei: Numerical methods for thermally stressed shallow shell equations (2019)
  14. Otmani, S. El; Rhin, G.; Sac-Épée, Jean-Marc: Finding new limit points of Mahler’s measure by genetic algorithms (2019)
  15. Rogov, Kirill; Pogromsky, Alexander; Steur, Erik; Michiels, Wim; Nijmeijer, Henk: Pattern analysis in networks of diffusively coupled Lur’e systems (2019)
  16. Tyler, Jonathan; Shiu, Anne; Walton, Jay: Revisiting a synthetic intracellular regulatory network that exhibits oscillations (2019)
  17. Wu, Qiong; Wang, Jin-He; Zhang, Hong-Wei; Wang, Shuang; Pang, Li-Ping: Nonsmooth optimization method for (H_\infty) output feedback control (2019)
  18. Costa, Giulio; Montemurro, Marco; Pailhès, Jérôme: A general hybrid optimization strategy for curve fitting in the non-uniform rational basis spline framework (2018)
  19. De Vincenzo, Ilario; Massari, Giovanni F.; Giannoccaro, Ilaria; Carbone, Giuseppe; Grigolini, Paolo: Mimicking the collective intelligence of human groups as an optimization tool for complex problems (2018)
  20. Gabelaia, A.: On the adjustment of Arrow-Hurwitz model in the frame of Walras general equilibrium theory (2018)

1 2 3 ... 12 13 14 next