nonlinear programming
An Augmented Lagrangian Algorithm for Engineering Optimization by Solving Nonlinear Programming Problem
... In this paper, we discuss about the Augmented Lagrangian Method (ALM) and its algorithm in engineering optimization which has many other interesting properties with supporting numerical and theoretical roles. These ...
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A Refinement on the Earlier Technique for Nonlinear Programming Problem in Fuzzy Environment
... Fuzzy nonlinear programming problem (FNLPP) is useful in solving problems which are difficult, impossible to solve due to the imprecise, subjective nature of the problem formulation or have an accurate ...
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Primal-Dual Path-Following Methods For Nonlinear Programming
... for nonlinear programming (NLP), which involves the mini- mization or maximization of a nonlinear objective function subject to constraints on the ...of nonlinear program are problems with ...
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An Exact Penalty Approach for Mixed Integer Nonlinear Programming Problems
... integer nonlinear programming (MINLP) problems by converting a general MINLP problem to a finite sequence of nonlinear programming (NLP) problems with only continuous ...
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Nonlinear Programming Algorithms for CAD Systems of Line Structure Routing
... problem is formalized as a system of linear inequalities [1,2] With the discrete representation of the unknown extremal ( the project line ) with sufficient for practical purposes accuracy we obtain the optimization ...
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Modified Gauss Elimination Technique for Separable Nonlinear Programming Problem
... Separable programming deals with such nonlinear programming problem in which the objective function as well as constraints are ...Separable Nonlinear Programming Problem (SNPP) is ...
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Comparative study of Optimization methods for Unconstrained Multivariable Nonlinear Programming Problems
... Surprisingly not much attention has been given to maximization of multivariable nonlinear programming problems by the scholars. So we have chosen to study maximization problems and to our pleasant surprise, ...
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Compromise allocations of biobjective nonlinear programming problem under partial responses
... sponse i.e. partial non response was first discussed by Tripathi and Khare (1997). They estimate the population mean in presence Maqbool and Pirzada (2005) discuss it in two variate stratified sample surveys and find out ...
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A Parametric Linearization Approach for Solving Zero One Nonlinear Programming Problems
... One of the conventional methods for solving zero-one nonlinear programming problem is to transform it to a linear programming problem. The main difficulty of this method is the very large number of ...
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Methods And Solvers Used For Solving Mixed Integer Linear Programming And Mixed Nonlinear Programming Problems: A Review
... In general, all the optimization problems that are available in the current scenario, necessitates the basic need for modelling the continuous variables and discrete variables using the Mixed Integer Linear Program ...
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A SUPERLINEARLY CONVERGENT SEQUENTIAL QUADRATICALLY CONSTRAINED QUADRATIC PROGRAMMING ALGORITHM FOR DEGENERATE NONLINEAR PROGRAMMING MIHAI ANITESCU
... A subproblem that has quadratic constraints is more dicult to solve than a subproblem with linear constraints, the latter being the case of Sequential Quadratic Programming algorithms [19]. One could of course ...
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Application of Nonlinear Programming for Identification of Mathematical Models of Corrosive Destruction of Structures
... Analysis of the results of calculation of coefficients of fractional-linear model throughout the spectrum of observations allows us to conclude the feasibility of imposing restrictions on the area of permissible ...
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Prediction by Nonlinear Programming of Relative Chemical Composition of Dietary Botanical Components.
... The purpose of this paper is to introduce, dem- onstrate, test, and use nonlinear programming tech- niques to predict relative chemical composition and energy val[r] ...
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Duality in nonlinear programming problems under fuzzy environment with exponential membership functions
... The paper is organized as follows. In Sect. 2, we construct a general fuzzy nonlinear programming problem and formulate its Mangasarian type dual. Further, we prove duality theorems using exponential ...
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A Java Expression Evaluator for Nonlinear Programming
... This API can be used to solve Nonlinear Programming Problems using the methods referred in section II, as pre- sented in [3] and [4]. Since this API was developed in Java, originally it only allowed the ...
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Nonlinear programming approach for optimal control problems
... Abstract—Optimal control problem, which is a dynamic optimization problem over a time horizon, is a practical problem in determining control and state trajectories to minimize a cost functional. The applications of this ...
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Generalized Augmented Lagrangian Problem and Approximate Optimal Solutions in Nonlinear Programming
... in nonlinear programming, establish dual function and dual problem based on the generalized augmented Lagrangian, obtain approximate KKT necessary optimal- ity condition of the generalized augmented ...
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A Feedback Neural Network for Solving Nonlinear Programming Problems with Hybrid Constraints
... introduce nonlinear programming problem with bound constraints and its equivalent formulation is ...solving nonlinear programming problems with hybrid constraints is given in Section ...
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A Novel Solution Approach using Linearization Technique for Nonlinear Programming Problems
... Linear Programming (SLP) which is one of the direct methods solves NLP problems approximately, and uses a se- ries of LP problems generated by using first order Taylor series expansions of objective functions and ...
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An efficient nonlinear programming method for eliciting preference weights of incomplete comparisons
... Bozóki et al. [10] developed a Non-Linear Programming (NLP) model to minimize max . Since they could not provide an efficient algorithm to solve this NLP model, they proposed the iterative method of cyclic ...
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