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Primal Superlinear Convergence of Sqp Methods in Piecewise Linear-Quadratic Composite Optimization
This paper mainly concerns with the primal superlinear convergence of the quasi-Newton sequential quadratic programming (SQP) method for piecewise...
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Sparse approximate solution of fitting surface to scattered points by MLASSO model
The goal of this paper is to achieve a computational model and corresponding efficient algorithm for obtaining a sparse representation of the fitting...
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Collaboration of Multiple Autonomous Industrial Robots through Optimal Base Placements
Multiple autonomous industrial robots can be of great use in manufacturing applications, particularly if the environment is unstructured and custom...
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Block spectral clustering for multiple graphs with inter-relation
Clustering methods for multiple graphs explore and exploit multiple graphs simultaneously to obtain a more accurate and robust partition of the data...
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An energy stable evolution method for simulating two-phase equilibria of multi-component fluids at constant moles, volume and temperature
In this paper, we propose an energy-stable evolution method for the calculation of the phase equilibria under given volume, temperature, and moles...
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Strategically supported cooperation in dynamic games with coalition structures
The problem of strategic stability of long-range cooperative agreements in dynamic games with coalition structures is investigated. Based on...
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A Hitchhiker’s Guide to Automatic Differentiation
This article provides an overview of some of the mathematical principles of Automatic Differentiation (AD). In particular, we summarise different...
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Adjoint-free calculation method for conditional nonlinear optimal perturbations
Adjoint-free calculation method is proposed to compute conditional nonlinear optimal perturbations (CNOP) combined with initial perturbations and...
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An approximate dynamic programming approachto decision making in the presence of uncertainty for surfactant-polymer flooding
The least squares Monte Carlo method is a decision evaluation method that can capture the effect of uncertainty and the value of flexibility of a...
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Optimal control of discrete and differential inclusions with distributed parameters in the gradient form
This paper is devoted to optimization of so-called first-order differential ( P C ) inclusions in the gradient form on a square domain. As a...
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Copositivity detection by difference-of-convex decomposition and ω-subdivision
We present three new copositivity tests based upon difference-of-convex (d.c.) decompositions, and combine them to a branch-and-bound algorithm of ω -s...
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A comparison of some methods for bounding connected and disconnected solution sets of interval linear systems
Finding bounding sets to solutions to systems of algebraic equations with uncertainties in the coefficients, as well as rapidly but rigorously...
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Using Computer Algebra to Certify the Global Convergence of a Numerical Optimization Process
The basic objective of blind signal separation is to recover a set of source signals from a set of observations that are mixtures of the sources with...
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An image-driven parameter estimation problem for a reaction–diffusion glioma growth model with mass effects
We present a framework for modeling gliomas growth and their mechanical impact on the surrounding brain tissue (the so-called, mass-effect). We...
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Symbolic Fenchel Conjugation
Of key importance in convex analysis and optimization is the notion of duality, and in particular that of Fenchel duality. This work explores...
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On the choice of parameters for the weighting method in vector optimization
We present a geometrical interpretation of the weighting method for constrained (finite dimensional) vector optimization. This approach is based on...
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The Cross-Entropy Method for Continuous Multi-Extremal Optimization
In recent years, the cross-entropy method has been successfully applied to a wide range of discrete optimization tasks. In this paper we consider the...
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Interval Arithmetic, Affine Arithmetic, Taylor Series Methods: Why, What Next?
In interval computations, the range of each intermediate result r is described by an interval r . To decrease excess interval width, we can keep some...
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On Fuzzy Input Data and the Worst Scenario Method
In practice, input data entering a state problem are almost always uncertain to some extent. Thus it is natural to consider a set U ad of admissible...