DIRECTGO: A new DIRECT-type MATLAB toolbox for derivative-free global optimization
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Abstract (arXiv)
In this work, we introduce DIRECTGO, a new MATLAB toolbox for derivative-free global optimization. DIRECTGO collects various deterministic derivative-free DIRECT-type algorithms for box-constrained, generally-constrained, and problems with hidden constraints. Each sequential algorithm is implemented in two ways: using static and dynamic data structures for more efficient information storage and organization. Furthermore, parallel schemes are applied to some promising algorithms within DIRECTGO. The toolbox is equipped with a graphical user interface (GUI), ensuring the user-friendly use of all functionalities available in DIRECTGO. Available features are demonstrated in detailed computational studies using a comprehensive DIRECTGOLib v1.0 library of global optimization test problems. Additionally, eleven classical engineering design problems illustrate the potential of DIRECTGO to solve challenging real-world problems. Finally, the appendix gives examples of accompanying MATLAB programs and provides a synopsis of its use on the test problems with box and general constraints.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Jul 2021.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 1; 2024: 0; 2025: 0; 2026: 1.
5 papers.
- 2021A diffusion-map-based algorithm for gradient computation on manifolds and applicationscited by 0
- 2022An Efficient Global Optimization Algorithm with Adaptive Estimates of the Local Lipschitz Constantscited by 0
- 2022Are metaheuristics worth it? A computational comparison between nature-inspired and deterministic techniques on black-box optimization problemscited by 0
- 2023Global and Preference-based Optimization with Mixed Variables using Piecewise Affine Surrogatescited by 0
- 2026A practical DIRECT-type algorithm for medium-scale black-box global optimizationcited by 0
- 2026A practical DIRECT-type algorithm for medium-scale black-box global optimization9 Sep 2026
- 2023Global and Preference-based Optimization with Mixed Variables using Piecewise Affine Surrogates9 Feb 2023
- 2022Are metaheuristics worth it? A computational comparison between nature-inspired and deterministic techniques on black-box optimization problems13 Dec 2022
- 2022An Efficient Global Optimization Algorithm with Adaptive Estimates of the Local Lipschitz Constants8 Nov 2022
- 2021A diffusion-map-based algorithm for gradient computation on manifolds and applications16 Aug 2021