Nonlinear Programming (NLP)
Nonlinear programming approach for optimal control problems
... of nonlinear programming (NLP) approach for solving optimal control problems is still a potential research ...of NLP model for optimal control problems is ...of NLP model approximates ...
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An Interval parameter Fuzzy Robust Nonlinear Programming Model for Water Quality Management
... inexact nonlinear programming models have been ...quadratic programming method, which incorporated interval-parameter programming, two- stage stochastic programming, and fuzzy quadratic ...
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Introducing a nonlinear programming model and using genetic algorithm to rank the alternatives in analytic hierarchy process
... The remainder of this paper is organized as follows. Section 2 provides brief preliminaries on AHP and GAs. In section 3, a NLP is proposed for determining the priorities of alternatives in AHP. Some features are ...
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Karmarkar's algorithm : a view from nonlinear programming
... A basic form of Karmarkar's algorithm is described in Section 2, and we note the role of the potential function and the "restrictive assumption" that the optimal value of the objective f[r] ...
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A Java Expression Evaluator for Nonlinear Programming
... Abstract—Finding the optimal value for a problem is usual in many areas of knowledge where in many cases it is needed to solve Nonlinear Optimization Problems. For some of those problems it is not possible to ...
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A Modified Interactive Stability Algorithm for Solving Multi Objective NLP Problems with Fuzzy Parameters in Its Objective Functions
... compromise programming algorithm to obtain the optimal stable solution of multi-objective nonlinear programming problems with fuzzy parameters in the objective func- ...
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Hybrid Smart Grid Connected Photovoltaic and Fuel System
... the nonlinear programming (NLP) optimization method was used to determine the maximum electrical efficiency of the grid-connected SOFC subject to the constraints of fuel utilization factor, stack ...
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Hydrogen Distribution in Refinery with Nonlinear Programming
... Abstract Growth of the world population, increasing demand for fossil fuel consumption and consequently increasing threat of global warming, has extended the need for production and use of clean fuels and normal hydrogen ...
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Transformation methods in nonlinear programming
... The importance of retaining the inverse Hessian estimates when solving (4.1) has been demonstrated by the results of Table 4.2. Algorithm 5.1, like the Murtagh- Sargent approach, must therefore preserve the distinction ...
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A New Lagrangian Multiplier Method on Constrained Optimization
... [6] X.-W. Du and Y.-L. Shang, “Exact Augmented Lagrange Function for Nonlinear Programming Problems with Ine- quality and Equality Constraints,” Applied Mathematics and Mechanics, Vol. 26, No. 12, 2005, pp. ...
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Fuzzy Goal Programming Approach in Selective Maintenance Reliability Model
... multi-objective Nonlinear Programming Problem (MONLPP) and a Fuzzy goal programming method is used to work out the compromise allocation in multi-objective selective maintenance reliability model in ...
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Duality in Nonlinear Fractional Programming Problem Using Fuzzy Programming and Genetic Algorithm
... considered nonlinear fractional programming problem with multiple ...of nonlinear fractional programming has been considered under fuzzy ...of nonlinear programming using ...
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A Novel Interactive Possibilistic Mixed Integer Nonlinear Model for Cellular Manufacturing Problem under Uncertainty
... To represent the practically and validity of the proposed interactive possibilistic mixed integer nonlinear programming model, an industrial numerical experiment inspired from a manufacturing company is ...
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A MPCC NLP Approach for an Electric Power Market Problem
... equivalent NLP problem. This formulation allows taking advantage of certain NLP algorithms fea- tures in order to obtain rapid local ...the NLP solver, because it allows testing its reliability and ...
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A Probabilistic Algorithm for Optimal Control Problem
... into nonlinear programing problem (NLP), and then a recently proposed stochastic algorithm called Probabilistic Global Search Johor (PGSJ) is considered for the solution of resultant ...
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NLP Lean Programming Framework: Developing NLP Applications More Effectively
... The user can use a Xbox 360 controller to an- notate the structure of natural language. This type of input device provides a more comfort- able and playful user experience and in conjunc- tion with the GUI design the ...
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An Efficient Parallel Substrate for Typed Feature Structures on Shared Memory Parallel Machines
... We propose an efficient programming environment for developing parallel NLP systems on shared-memory parallel machines, called the Parallel Substrate for Typed Feature Structures PSTFS..[r] ...
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Kathaa: A Visual Programming Framework for NLP Applications
... of NLP Resources by the use of Kathaa User Intervention modules, and also moved on to demonstrate visual analysis of dif- ferent classification approaches by using the Kathaa- Classification-Evaluation ...complex ...
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Survey on Speech Recognization Techniques. (Natural Language Processing)
... of NLP that has drawn much research attention, but where the results are yet to reach the general public with an acceptable level of performance, is the natural language question-answering ...
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Expert artificial intelligence-based natural language processing characterises childhood asthma
... reproducible and efficient asthma ascertainment methods results in inconsistent asthma cohorts and study results for clinical trials or other studies. We aimed to assess whether application of expert artificial ...
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