Global optimization advances in mixed-integer nonlinear programming, MINLP, and constrained derivative-free optimization, CDFO
This manuscript reviews recent advances in deterministic global optimization for Mixed-
Integer Nonlinear Programming (MINLP), as well as Constrained Derivative-Free …
Integer Nonlinear Programming (MINLP), as well as Constrained Derivative-Free …
Derivative-free optimization methods
In many optimization problems arising from scientific, engineering and artificial intelligence
applications, objective and constraint functions are available only as the output of a black …
applications, objective and constraint functions are available only as the output of a black …
Review and comparison of algorithms and software for mixed-integer derivative-free optimization
N Ploskas, NV Sahinidis - Journal of Global Optimization, 2022 - Springer
This paper reviews the literature on algorithms for solving bound-constrained mixed-integer
derivative-free optimization problems and presents a systematic comparison of available …
derivative-free optimization problems and presents a systematic comparison of available …
Mixed-integer nonlinear optimization
Many optimal decision problems in scientific, engineering, and public sector applications
involve both discrete decisions and nonlinear system dynamics that affect the quality of the …
involve both discrete decisions and nonlinear system dynamics that affect the quality of the …
SO-MI: A surrogate model algorithm for computationally expensive nonlinear mixed-integer black-box global optimization problems
This paper introduces a surrogate model based algorithm for computationally expensive
mixed-integer black-box global optimization problems with both binary and non-binary …
mixed-integer black-box global optimization problems with both binary and non-binary …
Surrogate-based optimization for mixed-integer nonlinear problems
SH Kim, F Boukouvala - Computers & Chemical Engineering, 2020 - Elsevier
Simulation-based optimization using surrogate models enables decision-making through
the exchange of data from high-fidelity models and development of approximations. Many …
the exchange of data from high-fidelity models and development of approximations. Many …
The mesh adaptive direct search algorithm for granular and discrete variables
C Audet, S Le Digabel, C Tribes - SIAM Journal on Optimization, 2019 - SIAM
The mesh adaptive direct search (Mads) algorithm is designed for blackbox optimization
problems for which the functions defining the objective and the constraints are typically the …
problems for which the functions defining the objective and the constraints are typically the …
A linesearch-based derivative-free approach for nonsmooth constrained optimization
In this paper, we propose new linesearch-based methods for nonsmooth constrained
optimization problems when first-order information on the problem functions is not available …
optimization problems when first-order information on the problem functions is not available …
BFO, a trainable derivative-free brute force optimizer for nonlinear bound-constrained optimization and equilibrium computations with continuous and discrete …
M Porcelli, PL Toint - ACM Transactions on Mathematical Software …, 2017 - dl.acm.org
A direct-search derivative-free Matlab optimizer for bound-constrained problems is
described, whose remarkable features are its ability to handle a mix of continuous and …
described, whose remarkable features are its ability to handle a mix of continuous and …
Global optimization for mixed categorical-continuous variables based on Gaussian process models with a randomized categorical space exploration step
M Munoz Zuniga, D Sinoquet - INFOR: Information Systems and …, 2020 - Taylor & Francis
Real industrial studies often give rise to complex optimization problems involving mixed
variables and time consuming simulators. To deal with these difficulties we propose the use …
variables and time consuming simulators. To deal with these difficulties we propose the use …