DOT - Design Optimization Tools. DOT is a general-purpose gradient-based optimization software library that can be used to solve a wide variety of optimization problems. Users have to link the DOT library into their own program. DOT provides the optimization technology, while the rest of the program has to provide the required function evaluations needed to perform the optimization. These function evaluations can be linear or nonlinear functions of the design variables. They may be very simple analytical functions or may be highly complicated implicit functions, for example a non-linear structural finite element simulation. Very little formal knowledge of optimization techniques is needed to make efficient use of DOT. DOT can handle constrained, unconstrained, linear and non-linear optimization problems and can automatically calculate finite difference gradients needed during the optimization. DOT can also deal with user supplied gradients.

References in zbMATH (referenced in 62 articles )

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  1. Taheri, Alireza H.; Suresh, Krishnan: Adaptive (w)-refinement: a new paradigm in isogeometric analysis (2020)
  2. Morlando, Fabrizio: Adjoint-based sensitivity analysis by panel methods and CAS (2017)
  3. Trindade, Graça; Dias, José G.; Ambrósio, Jorge: Extracting clusters from aggregate panel data: a market segmentation study (2017)
  4. Naanaa, Anis: Fast chaotic optimization algorithm based on spatiotemporal maps for global optimization (2015)
  5. Ren, Xuchun; Rahman, Sharif: Robust design optimization by polynomial dimensional decomposition (2013)
  6. Yumuşak, Mine: Analysis and design optimization of solid rocket motors in viscous flows (2013)
  7. Talatahari, S.; Kaveh, A.; Sheikholeslami, R.: Engineering design optimization using chaotic enhanced charged system search algorithms (2012)
  8. Trindade, Graça; Ambrósio, Jorge: An optimization method to estimate models with store-level data: a case study (2012)
  9. Yim, JinWoo; Lee, Byung Joon; Kim, Chongam: Exploring multi-stage shape optimization strategy of multi-body geometries using Kriging-based model and adjoint method (2012)
  10. Yumuşak, M.; Eyi, S.: Design optimization of rocket nozzles in chemically reacting flows (2012)
  11. Edke, Mangesh S.; Chang, Kuang-Hua: Shape optimization for 2-D mixed-mode fracture using extended FEM (XFEM) and level set method (LSM) (2011) ioport
  12. Eyi, Sinan; Ezertas, Alper; Yumusak, Mine: Design optimization in non-equilibrium reacting flows (2011)
  13. Gur, Ohad; Bhatia, Manav; Mason, William H.; Schetz, Joseph A.; Kapania, Rakesh K.; Nam, Taewoo: Development of a framework for truss-braced wing conceptual MDO (2011) ioport
  14. Ha, Youn Doh; Kim, Min-Geun; Kim, Hyun-Seok; Cho Seonho: Shape design optimization of SPH fluid-structure interactions considering geometrically exact interfaces (2011)
  15. Park, Gyung-Jin: Technical overview of the equivalent static loads method for non-linear static response structural optimization (2011) ioport
  16. Kim, Yong-Il; Park, Gyung-Jin: Nonlinear dynamic response structural optimization using equivalent static loads (2010)
  17. Yang, Dixiong; Yang, Pixin: Numerical instabilities and convergence control for convex approximation methods (2010)
  18. Arroyo, Sharon F.; Cramer, Evin J.; John, E. jun. Dennis; Frank, Paul D.: Comparing problem formulations for coupled sets of components (2009)
  19. Fallahian, S.; Hamidian, D.; Seyedpoor, S. M.: Optimal design of structures using the simultaneous perturbation stochastic approximation algorithm (2009)
  20. Bergamaschi, Paulo Roberto; de Fátima Pereira Saramago, Sezimária; dos Santos Coelho, Leandro: Comparative study of SQP and metaheuristics for robotic manipulator design (2008)

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