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Showing 1 to 20 of 143 for “"Nonlinear programming"”.
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Quasi-Newton Methods for Nonlinear Programming
… updates for use in a quasi-Newton method for nonlinear programming. We show how these updates model the underlying nonlinear equation better than the standard symmetric updates and also how they require less overall work for large problems.
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Global Optimization for Constrained Nonlinear Programming
Finally, we apply CSA to solve a collection of engineering application benchmarks and design filters for subband image coding. Much better results have been reported in comparison with other existing methods.
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Rate of convergence in nonlinear programming
… rate of convergence of a few algorithms used for nonlinear programming problems. The Newton-Raphson procedure and a higher order procedure used for the solution of nonlinear equations is studied. Both the convergence and the rate of convergence for the multivariate Newton-Raphson procedure is …
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An active-constraint logic for nonlinear programming
… logic was tested computationally using quadratic programming problems. Three existing active-set strategies were used for comparision. The proposed logic almost always performed as well or better than the best among the three existing active-set strategies.
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On cutting planes for mixed-integer nonlinear programming
Mixed-integer nonlinear programming is a powerful technology that allows us to model and solve problems involving nonlinear functions, continuous, and discrete variables. The state-of-the-art solvers of mixed-integer nonlinear programs (MINLPs) use a combination of, among other techniques, branch- …
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A study of optimal load flow using nonlinear programming
Power systems optimal load flow studies are performed for standard test cases using several methods of minimization. Comparisons of the solutions are made based on digital computer results. A general discussion is made of optimization and the necessary conditions for solution. Cost functions are …
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PARALLEL ALGORITHMS FOR NONLINEAR PROGRAMMING AND APPLICATIONS IN PHARMACEUTICAL MANUFACTURING
… are required. The demand for fast solution of nonlinear optimization problems, coupled with the emergence of new concurrent computing architectures, drives the need for parallel algorithms to solve challenging NLP problems. The goal of this work is the development of parallel algorithms for …
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Collocation With Nonlinear Programming for Two-Sided Flight Path Optimization
… The method of direct collocation with nonlinear programming is extended to find the solution of a zerosum two-person differential game by incorporating the analytical optimality condition for one player into the system equations. The new method is named semi-direct collocation with …
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Nonlinear Programming and Multiparameter Sensitivity in Linear Time-Invariant Networks
Made available in DSpace on 2014-12-08T22:24:00Z (GMT). No. of bitstreams: 1 6612360.pdf: 1707781 bytes, checksum: 8526ab5a18aba82f6e81465b1d9e6559 (MD5) Previous issue date: 1966
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Two-Stage Stochastic Mixed Integer Nonlinear Programming: Theory, Algorithms, and Applications
… for solving them. Two-stage stochastic programming is one of the powerful modeling tools that allows probabilistic data parameters in mixed integer programming, a well-known tool for optimization modeling with deterministic input data. However, akin to the mixed integer programs, these …
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Optimal finite-thrust spacecraft trajectories using direct transcription and nonlinear programming
… the equations of motion to derive a mathematical programming problem which approximates the optimal control problem, and which is solved numerically. This conversion is referred to as ""transcription."" Transcription methods were developed in the sixties and seventies; however, for nonlinear …
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Neighboring Optimal Feedback Control for Trajectories Found by Collocation and Nonlinear Programming
On August 9, 1995, because of a launch vehicle failure the Koreasat 1 satellite was placed into an orbit that was 3,400 nautical miles (6,351 km) lower than the planned geostationary transfer orbit. The Lockheed-Martin company rescue team performed a plan which did put the satellite on station but …
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Methods for Solving Generalized Systems of Inequalities With Application to Nonlinear Programming
… of equations and inequalities, solving general nonlinear complementarity problems, and finding Karush-Kuhn-Tucker points for mathematical programs.
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Optimization of stationary expansion planning and transient network control by mixed-integer nonlinear programming
… are located in the field of Mixed-Integer Nonlinear Programming (MINLP). However, global state-of-the-art MINLP solvers are not mature enough to solve or even find primal solutions on large-scale real-world instances since the resulting degree of nonconvexity and nonlinearity pose principal …
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Enhancing tractability of mixed-integer nonlinear programming models: case studies in energy and sports
We address three integer-programming models which are difficult to formulate and solve because, fundamentally, they are mixed-integer, nonlinear programs. These three applications are: (i) design of and dispatch for a forward operating base, or remote military installation, that possesses a …
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Solving asymmetric variational inequality problems and systems of equations with generalized nonlinear programming algorithms
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1985.
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Trajectory optimization for a fixed trim re-entry vehicle using direct collocation with nonlinear programming
… problem is solved using the MINOS non-linear programming software package. The resulting collocation guidance software is tested using data for the Kistler K-1 vehicle system and an existing vehicle simulation. Mass, wind, density, and entry angle dispersions are considered, as are various …
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Stochastic Optimization Powered by Markov Chain Monte Carlo: Mixed-Integer Nonlinear Programming for Communications Network Scheduling
<p>Markov chain Monte Carlo methods are known for their effectiveness with a multitude of complex mathematical problems, including those in mixed spaces of continuous and discrete components. In this dissertation, we examine variations of complicated scheduling problems involving allocating …
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Sensitivity Constrained Nonlinear Programming: A General Approach for Planning and Design Under Parameter Uncertainty and an Application to Treatment Plant Design
… A general approach, Sensitivity Constrained Nonlinear Programming (SCNLP), was developed for extending nonlinear optimization models, to include functions that depend on the system sensitivity to changes in parameter values. Such sensitivity-based functions include first-order measures of …
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