State-of-the-art survey—constrained nonlinear 0–1 programming
… maximization problems in 0—1 … to nonlinear terms in the objective functions and / or
constraints. Nonlinear terms also appear in the latter when expressing complex logical constraints …
constraints. Nonlinear terms also appear in the latter when expressing complex logical constraints …
State-of-the-art in parallel nonlinear optimization
FA Lootsma, KM Ragsdell - Parallel Computing, 1988 - Elsevier
… special problems and methods in constrained optimization: … method for minimizing a non-linear
objective function f over the … We study parallel optimization problems for various reasons (…
objective function f over the … We study parallel optimization problems for various reasons (…
A literature review: solving constrained non-linear bi-level optimization problems with classical methods
… on applying different classical approaches in solving constrained non-linear, bi-level
optimization problems considering continuous design variables and no discontinuity in functions. …
optimization problems considering continuous design variables and no discontinuity in functions. …
State-of-the-art reviews of meta-heuristic algorithms with their novel proposal for unconstrained optimization and applications
RP Parouha, P Verma - Archives of Computational Methods in …, 2021 - Springer
… equation (by introducing a non-linear decreasing factor. And in … unconstrained optimization
problems in this present study. … , constrained as well as unconstrained optimization problems. …
problems in this present study. … , constrained as well as unconstrained optimization problems. …
Handbook of nature-inspired optimization algorithms: the state of the art: Volume II: solving constrained single objective real-parameter optimization problems
… Method for Non-linear Programming Problems with Equality Constraints”, a new type …
algorithm is used to solve the Non-Linear Programming Problems (NLPP) with equality constraints …
algorithm is used to solve the Non-Linear Programming Problems (NLPP) with equality constraints …
An efficient modified differential evolution algorithm for solving constrained non-linear integer and mixed-integer global optimization problems
AW Mohamed - International Journal of Machine Learning and …, 2017 - Springer
… and four state-of-the-art evolutionary algorithms are … algorithms in solving these test problems.
Furthermore, EMDE exhibits good performance in solving two high-dimensional problems, …
Furthermore, EMDE exhibits good performance in solving two high-dimensional problems, …
An overview of unconstrained optimization
R Fletcher - Algorithms for continuous optimization: The state of the …, 1994 - Springer
… different approach more related to constrained optimization. The minimization of nonsmooth
… large scale optimization. Frequently however a large scale optimization problem has some …
… large scale optimization. Frequently however a large scale optimization problem has some …
Constraint handling techniques for metaheuristics: a state-of-the-art review and new variants
ND Lagaros, M Kournoutos, NA Kallioras… - Optimization and …, 2023 - Springer
… for solving unconstrained NP-complete problems, and hence their application to constrained
optimization problems (… of performance and bound constraints. While considerable research …
optimization problems (… of performance and bound constraints. While considerable research …
Mixed-integer nonlinear optimization
… Third, we survey the state of the art in software for MINLP. … with the challenges of handling
nonlinear functions. MINLP is … maximization and more general constraints, such as equality …
nonlinear functions. MINLP is … maximization and more general constraints, such as equality …
Nonlinear programming solvers for unconstrained and constrained optimization problems: a benchmark analysis
… for the solution of nonlinear programming problems. With this … and constrained nonlinear
programming problems. The … of 23 algorithms to solve 60 benchmark problems. To enrich …
programming problems. The … of 23 algorithms to solve 60 benchmark problems. To enrich …
