constrained nonlinear optimization problem
A nonmonotone flexible filter method for nonlinear constrained optimization
... There are various methods for solving the inequality constrained nonlinear optimization problem (P). For example, sequential quadratic programming methods, trust region ap- proaches [], ...
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Simple Optimization (SOPT) for Nonlinear Constrained Optimization Problem
... for constrained optimization having different characteristic are ...different optimization techniques such as League championship algorithm(LCA), Particle swarm optimization(PSO), Artificial ...
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Trajectory Optimization for Chance-Constrained Nonlinear Stochastic Systems
... SNOC problem. The method involves deriving a deterministic nonlinear op- timal control (DNOC) problem with convex constraints that are a surrogate to the SNOC problem by systematically ac- ...
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A modified exact smooth penalty function for nonlinear constrained optimization
... a constrained nonlinear programming problem by augmenting the dimension of the program with a variable that controls the weight of the penalty ...original constrained problem are ...
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Numerical Solution for PDE Constrained Optimization Problem in Cardiac Electrophysiology
... The monodomain model is a well-established mathematical model for numerical simulation of cardiac electrical activity [4, 5]. It consists of a parabolic partial differential equation (PDE) coupled with a system of ...
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Framework for the buckling optimisation of variable-angle-tow composite plates
... an optimization framework that employs B-splines to define the spatial variation of lamination parameters (variable ...fully constrained inside the feasible region, provided that the lamination parameters ...
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Solving Nonlinear Constrained Optimization Time Delay Systems with a Direct Transcription Approach.
... Sparse Nonlinear OPTimizer (SNOPT) [61], Interior Point OPTimizer (IPOPT) [145], or Matlab’s embedded NLP solver ...control problem using Lobatto IIIA ...
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Primal dual interior point QP free algorithm for nonlinear constrained optimization
... iterate k, two SLEs are solved to yield a master search direction. Then a least squares problem (LSP) needs to be solved to avoid the so-called Maratos effect []. However, the SLEs solved in [] may become ...
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Constrained Nonlinear Model Predictive Control of a Polymerization Process via Evolutionary Optimization
... online optimization but in the case of unconstrained linear plants, closed form solutions can be derived ...real-time) constrained optimization problem has to be solved in each sampling ...
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Trade off curve of an emission economic load dispatch using NSGA II and PVDE
... for nonlinear constrained environmental economic load dispatch problem which is the combination of Non-dominated Sorting Genetic Algorithm (NSGA-II) and Population Variant Differential Evolution ...
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Research Article Heuristic-Based Firefly Algorithm for Bound Constrained Nonlinear Binary Optimization
... A new sigmoid “erf” function is proposed. In the context of the firefly algorithm, three different implementations aiming to incorporate the heuristics for binary variables into FA are proposed (mCS, mBS, and pBC). Based ...
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A New Lagrangian Multiplier Method on Constrained Optimization
... the nonlinear inequality constrained optimization problem (NLP), there are many practical methods to solve it, such as augmented Lagrangian function method [1-6], Trust-region filter method ...
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A new filter QP free method for the nonlinear inequality constrained optimization problem
... smooth optimization problem with smooth inequality ...the nonlinear complementarity problem for the Karush–Kuhn–Tucker optimality ...the nonlinear complementarity problem in the ...
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Solving nonlinear optimization problems with bipolar fuzzy relational equation constraints
... tions constrained optimization problem based on this alternative ...an optimization problem can be further re- duced to a - integer linear optimization problem when it ...
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Metaheuristic research: a comprehensive survey
... tough optimization problems, Yang [89] asserts that it is hard to affirm mathematically why metaheuristic algorithms are that ...open problem residing both in theory and ...
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Higher Order Weakly Generalized Adjacent Epiderivatives and Applications to Duality of Set Valued Optimization
... A new notion of higher-order weakly generalized adjacent epiderivative for a set-valued map is introduced. By virtue of the epiderivative and weak minimality, a higher-order Mond-Weir type dual problem and a ...
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Solving multiobjective constrained trajectory optimization problem by an extended evolutionary algorithm
... evolutionary-based optimization techniques have become popular and have been widely imple- mented to address optimal trajectory design ...a constrained space plane reentry trajectory design problem ...
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An Advanced Ant Colony Algorithm for Constrained Multi objective Optimization Problem
... swarm optimization (PSO) [7], neighborhood search algorithm (NS) [16], artificial bee colony algorithm (ABC) [17-18], simulated annealing algorithm (SA) [19] ...
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An over constrained optimization problem: The prolonged autonomy bike (pa bike)
... Even with the commercial components available, that are far from optimized for the specific application, the PA-bike is not only feasible, but also extremely convenient. A daily usage even on medium distances for the ...
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A FORMAL DEFINITION OF METRICS FOR OBJECT ORIENTED DESIGN: MOOD METRICS
... The artificial bee colony algorithm (ABC), proposed by Karaboga, is recently introduced optimization algorithm which simulates the foraging behavior of a honey bee colony. In ABC algorithm, the swarm population ...
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