BookDOI
Numerische Mathematik 1
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The article was published on 1989-01-01. It has received 2186 citations till now.read more
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Book ChapterDOI
A Lagrangian Relaxation of the Capacitated Multi-Item Lot Sizing Problem Solved with an Interior Point Cutting Plane Algorithm
TL;DR: In this article, a Lagrangian relaxation of the capacity constraints is used in two ways: first, it generates a lower bound for the optimal value, and second, the primal and dual solutions of the relaxation (if available) are used to generate integer feasible solutions by primal or dual heuristics.
Proceedings ArticleDOI
Pseudo-transient Continuation, Solution Update Methods, and CFL Strategies for DG Discretizations of the RANS-SA Equations
TL;DR: The pseudo-time continuation method derived from the backward Euler scheme in its constrained and unconstrained versions are considered and solution update methods based on line-search are proposed and tested in combination with dierent CFL evolution strategies.
Journal ArticleDOI
A proximal cutting plane method using Chebychev center for nonsmooth convex optimization
TL;DR: An algorithm is developed for minimizing nonsmooth convex functions by extending Elzinga–Moore cutting plane algorithm by enforcing the search of the next test point not too far from the previous ones, thus removing compactness assumption.
Journal ArticleDOI
Solution of Chemical Dynamic Optimization Using the Simultaneous Strategies
Xinggao Liu,Long Chen,Yunqing Hu +2 more
TL;DR: The proposed approach becomes more efficient in adjusting elements to track optimal control profile breakpoints and ensure accurate state and control profiles and the research results reveal that the proposed approach is preferable in improving the solution accuracy of chemical dynamic optimization problem.
Proceedings ArticleDOI
From sBoW to dCoT marginalized encoders for text representation
TL;DR: This paper proposes Dense Cohort of Terms (dCoT), an unsupervised algorithm to learn improved sBoW document features and demonstrates empirically, on several benchmark datasets, that dCoT features significantly improve the classification accuracy across several document classification tasks.