OPTI: lowering the barrier between open source optimizers and the industrial MATLAB user. or those interested in tackling industrial optimization problems, typical approaches include either purchasing a sophisticated and often specialised solver perhaps with accompanying consulting support, using an internet-based optimization server or using a Matlab toolbox. While there are a number of open source optimization solvers that enable one to solve a wide range of continuous and discrete, linear and nonlinear, medium and large-scale optimization problems, only a few contain useable pre-compiled binaries for Windows. The initiative described in this work, Opti , bridges this gap by providing an intuitive object-based general optimization platform that interfaces with many of those freely available, and those with low or no-cost licence requirements, high-quality optimization codes all accessible within the rapid development environment Matlab. The user needs not compile or build the various tools, but still leverages off the advantages of using high-end desktop hardware (such as 64bit multi-core processors) and remaining in a powerful and familiar development environment.

References in zbMATH (referenced in 30 articles )

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  1. Jian, Jinbao; Liu, Pengjie; Yin, Jianghua; Zhang, Chen; Chao, Miantao: A QCQP-based splitting SQP algorithm for two-block nonconvex constrained optimization problems with application (2021)
  2. Bhosekar, Atharv; Ierapetritou, Marianthi: A discontinuous derivative-free optimization framework for multi-enterprise supply chain (2020)
  3. Jian, Jinbao; Zhang, Chen; Yin, Jianghua; Yang, Linfeng; Ma, Guodong: Monotone splitting sequential quadratic optimization algorithm with applications in electric power systems (2020)
  4. Kronqvist, Jan; Bernal, David E.; Grossmann, Ignacio E.: Using regularization and second order information in outer approximation for convex MINLP (2020)
  5. Tueros, Juan Alberto Rojas; Horowitz, Bernardo; Willmersdorf, Ramiro Brito; de Oliveira, Diego Felipe Barbosa: Refined ensemble-based waterflooding optimization subject to field-wide constraints (2020)
  6. Ahn, Chi Young; Yun, Sangwoon: A mathematical model for the 3D location estimation of 2D echocardiography data (2019)
  7. Liu, Kanglin; Wang, Meng; Zhang, Zhi-Hai: An outer approximation algorithm for capacitated disassembly scheduling problem with parts commonality and random demand (2019)
  8. Pecci, Filippo; Abraham, Edo; Stoianov, Ivan: Global optimality bounds for the placement of control valves in water supply networks (2019)
  9. Wang, Shi’an; Ahmed, N. U.: Optimum management of the network of city bus routes based on a stochastic dynamic model (2019)
  10. Ahn, Chi Young; Yun, Sangwoon: A study on the 3D position estimation of ventricular borders extracted from 2D echocardiography data (2018)
  11. Bánhelyi, Balázs; Csendes, Tibor; Lévai, Balázs; Pál, László; Zombori, Dániel: The GLOBAL optimization algorithm. Newly updated with Java implementation and parallelization (2018)
  12. Carli, Raffaele; Dotoli, Mariagrazia; Pellegrino, Roberta: A decision-making tool for energy efficiency optimization of street lighting (2018)
  13. Csercsik, Dávid; Kiss, Hubert János: Optimal payments to connected depositors in turbulent times: a Markov chain approach (2018)
  14. Hare, Warren; Loeppky, Jason; Xie, Shangwei: Methods to compare expensive stochastic optimization algorithms with random restarts (2018)
  15. Lee, Jae Hyoung; Lee, Gue Myung: On minimizing difference of a SOS-convex polynomial and a support function over a SOS-concave matrix polynomial constraint (2018)
  16. Liu, Kanglin; Zhang, Zhi-Hai: Capacitated disassembly scheduling under stochastic yield and demand (2018)
  17. Moye, Matthew J.; Diekman, Casey O.: Data assimilation methods for neuronal state and parameter estimation (2018)
  18. Müller, Juliane; Woodbury, Joshua D.: GOSAC: global optimization with surrogate approximation of constraints (2017)
  19. Pál, László: Empirical study of the improved UNIRANDI local search method (2017)
  20. Papp, Dávid: Semi-infinite programming using high-degree polynomial interpolants and semidefinite programming (2017)

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