minpack

Notes on optimization software. This paper is an attempt to indicate the current state of optimization software and the search directions which should be considered in the near future. There are two parts of this paper. In the first part I discuss some of the issues that are relevant to the development of general optimization software. I have tried to focus on those issues which do not seem to have received sufficient attention and which would significantly benefit from further research. In addition, I have chosen issues that are particularly relevant to the development of software for optimization libraries. In the second part I illustrate some of the points raised in the first part by discussing algorithms for unconstrained optimization. Because the discussion in this part is brief, the interested reader may want to consult other papers in this volume for further information. In both parts my comments are influenced by my involvement in the MINPACK project and by my experiences in the development of MINPACK-1 [cf. the author, B. S. Garbow and K. E. Hillstrom, ACM Trans. Math. Software 7, 17-41 (1981; Zbl 0454.65049)]. (Source: http://plato.asu.edu)


References in zbMATH (referenced in 712 articles , 2 standard articles )

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  1. Wang, Qifeng; Li, Weiguo; Bao, Wendi; Gao, Xingqi: Nonlinear Kaczmarz algorithms and their convergence (2022)
  2. Abubakar, Auwal Bala; Muangchoo, Kanikar; Ibrahim, Abdulkarim Hassan; Abubakar, Jamilu; Rano, Sadiya Ali: FR-type algorithm for finding approximate solutions to nonlinear monotone operator equations (2021)
  3. Assunção, P. B.; Ferreira, O. P.; Prudente, L. F.: Conditional gradient method for multiobjective optimization (2021)
  4. Audet, Charles; Bigeon, Jean; Couderc, Romain: Combining cross-entropy and MADS methods for inequality constrained global optimization (2021)
  5. Birgin, E. G.; Martínez, J. M.; Ramos, A.: On constrained optimization with nonconvex regularization (2021)
  6. Fang, Minglei; Wang, Min; Sun, Min; Chen, Rong: A modified hybrid conjugate gradient method for unconstrained optimization (2021)
  7. Fischer, A.; Izmailov, A. F.; Solodov, M. V.: Accelerating convergence of the globalized Newton method to critical solutions of nonlinear equations (2021)
  8. Grapiglia, Geovani N.; Sachs, Ekkehard W.: A generalized worst-case complexity analysis for non-monotone line searches (2021)
  9. Hansen, Nikolaus; Auger, Anne; Ros, Raymond; Mersmann, Olaf; Tušar, Tea; Brockhoff, Dimo: COCO: a platform for comparing continuous optimizers in a black-box setting (2021)
  10. Li, Xiangli; Zhao, Wenjuan; Dong, Xiaoliang: A new CG algorithm based on a scaled memoryless BFGS update with adaptive search strategy, and its application to large-scale unconstrained optimization problems (2021)
  11. Luo, Xin-long; Xiao, Hang: Generalized continuation Newton methods and the trust-region updating strategy for the underdetermined system (2021)
  12. Price, C. J.; Reale, M.; Robertson, B. L.: \textscOscars-II: an algorithm for bound constrained global optimization (2021)
  13. Yahaya, Mahmoud Muhammad; Kumam, Poom; Awwal, Aliyu Muhammed; Aji, Sani: A structured quasi-Newton algorithm with nonmonotone search strategy for structured NLS problems and its application in robotic motion control (2021)
  14. Zhu, Honglan; Ni, Qin; Jiang, Jianlin; Dang, Chuangyin: A new alternating direction trust region method based on conic model for solving unconstrained optimization (2021)
  15. Bahrami, Somayeh; Amini, Keyvan: An efficient two-step trust-region algorithm for exactly determined consistent systems of nonlinear equations (2020)
  16. Bergou, El Houcine; Diouane, Youssef; Kungurtsev, Vyacheslav: Convergence and complexity analysis of a Levenberg-Marquardt algorithm for inverse problems (2020)
  17. Bergou, El Houcine; Gorbunov, Eduard; Richtárik, Peter: Stochastic three points method for unconstrained smooth minimization (2020)
  18. Birgin, E. G.; Gardenghi, J. L.; Martínez, J. M.; Santos, S. A.: On the use of third-order models with fourth-order regularization for unconstrained optimization (2020)
  19. Boutet, Nicolas; Haelterman, Rob; Degroote, Joris: Secant update version of quasi-Newton PSB with weighted multisecant equations (2020)
  20. Chen, Liang; Ma, Yanfang: Shamanskii-like Levenberg-Marquardt method with a new line search for systems of nonlinear equations (2020)

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