Solving shortest length least-squares problems via dynamic programming
نویسندگان
چکیده
منابع مشابه
Solving polynomial least squares problems via semidefinite programming relaxations
A polynomial optimization problem whose objective function is represented as a sum of positive and even powers of polynomials, called a polynomial least squares problem, is considered. Methods to transform a polynomial least squares problem to polynomial semidefinite programs to reduce degrees of the polynomials are discussed. Computational efficiency of solving the original polynomial least sq...
متن کاملSolving Rank-Deficient Linear Least-Squares Problems*
Numerical solution of linear least-squares problems is a key computational task in science and engineering. Effective algorithms have been developed for the linear least-squares problems in which the underlying matrices have full rank and are well-conditioned. However, there are few efficient and robust approaches to solving the linear least-squares problems in which the underlying matrices are...
متن کاملA dynamic programming approach for solving nonlinear knapsack problems
Nonlinear Knapsack Problems (NKP) are the alternative formulation for the multiple-choice knapsack problems. A powerful approach for solving NKP is dynamic programming which may obtain the global op-timal solution even in the case of discrete solution space for these problems. Despite the power of this solu-tion approach, it computationally performs very slowly when the solution space of the pr...
متن کاملOn Solving Dynamic Shortest Path Problems
Given a dynamic network with n nodes and m arcs in which all attributes including travel times, travel costs and waiting costs may change dynamically over a time horizon T. The dynamic shortest path problem is to determine a path from a specified source node to every other node with minimal total cost, subject to the constraint that the total traverse time is at most T. This problem can be form...
متن کاملLinear Least Least Simplified Neural Networks for Solving Squares Problems in Real Time Squares and Total
In this paper a new class of simplified low-cost analog artificial neural networks with on chip adaptive learning algorithms are proposed for solving linear systems of algebraic equations in real time. The proposed learning algorithms for linear least squares (LS), total least squares (TLS) and data least squares (DLS) problems can be considered as modifications and extensions of well known alg...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Optimization Theory and Applications
سال: 1995
ISSN: 0022-3239,1573-2878
DOI: 10.1007/bf02193059