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NPSOL
NPSOL is a software package that performs numerical optimization. It solves nonlinear constrained problems using the sequential quadratic programming algorithm. It was written in Fortran by Philip Gill of UCSD and Walter Murray, Michael Saunders and Margaret Wright of Stanford University. The name derives from a combination of NP for nonlinear programming In mathematics, nonlinear programming (NLP) is the process of solving an optimization problem where some of the constraints or the objective function are nonlinear. An optimization problem is one of calculation of the extrema (maxima, minima or st ... and SOL, the Systems Optimization Laboratory at Stanford. References {{Citation , last = Gill , first = Philip , last2 = Murray , first2 = Walter , last3 = Saunders , first3 = Michael , last4 = Wright , first4 = Margaret , title = User's Guide for NPSOL 5.0: A Fortran Package for Nonlinear Programming , work = Technical Report SOL 86-6 , date = 4 J ...
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Sequential Quadratic Programming
Sequential quadratic programming (SQP) is an iterative method for constrained nonlinear optimization. SQP methods are used on mathematical problems for which the objective function and the constraints are twice continuously differentiable. SQP methods solve a sequence of optimization subproblems, each of which optimizes a quadratic model of the objective subject to a linearization of the constraints. If the problem is unconstrained, then the method reduces to Newton's method for finding a point where the gradient of the objective vanishes. If the problem has only equality constraints, then the method is equivalent to applying Newton's method to the first-order optimality conditions, or Karush–Kuhn–Tucker conditions, of the problem. Algorithm basics Consider a nonlinear programming problem of the form: :\begin \min\limits_ & f(x) \\ \mbox & b(x) \ge 0 \\ & c(x) = 0. \end The Lagrangian for this problem is :\mathcal(x,\lambda,\sigma) = f(x) - \lambda b(x) - \sigma c(x), w ...
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UCSD
The University of California, San Diego (UC San Diego or colloquially, UCSD) is a public land-grant research university in San Diego, California. Established in 1960 near the pre-existing Scripps Institution of Oceanography, UC San Diego is the southernmost of the ten campuses of the University of California, and offers over 200 undergraduate and graduate degree programs, enrolling 33,096 undergraduate and 9,872 graduate students. The university occupies near the coast of the Pacific Ocean, with the main campus resting on approximately . UC San Diego is ranked among the best universities in the world by major college and university rankings. UC San Diego consists of twelve undergraduate, graduate and professional schools as well as seven undergraduate residential colleges. It received over 140,000 applications for undergraduate admissions in Fall 2021, making it the second most applied-to university in the United States. UC San Diego Health, the region's only academic health s ...
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Stanford University
Stanford University, officially Leland Stanford Junior University, is a Private university, private research university in Stanford, California. The campus occupies , among the largest in the United States, and enrolls over 17,000 students. Stanford is considered among the most prestigious universities in the world. Stanford was founded in 1885 by Leland Stanford, Leland and Jane Stanford in memory of their only child, Leland Stanford Jr., who had died of typhoid fever at age 15 the previous year. Leland Stanford was a List of United States senators from California, U.S. senator and former List of governors of California, governor of California who made his fortune as a Big Four (Central Pacific Railroad), railroad tycoon. The school admitted its first students on October 1, 1891, as a Mixed-sex education, coeducational and non-denominational institution. Stanford University struggled financially after the death of Leland Stanford in 1893 and again after much of the campus was ...
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Nonlinear Programming
In mathematics, nonlinear programming (NLP) is the process of solving an optimization problem where some of the constraints or the objective function are nonlinear. An optimization problem is one of calculation of the extrema (maxima, minima or stationary points) of an objective function over a set of unknown real variables and conditional to the satisfaction of a system of equalities and inequalities, collectively termed constraints. It is the sub-field of mathematical optimization that deals with problems that are not linear. Applicability A typical non-convex problem is that of optimizing transportation costs by selection from a set of transportation methods, one or more of which exhibit economies of scale, with various connectivities and capacity constraints. An example would be petroleum product transport given a selection or combination of pipeline, rail tanker, road tanker, river barge, or coastal tankship. Owing to economic batch size the cost functions may have disconti ...
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