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Mathematische Operationsforschung und Statistik Series Optimization is a peer-reviewed journal published by Taylor & Francis, covering Advanced Optimization Algorithms Research, Optimization and Variational Analysis, Physics and Engineering Research Articles.
| Publisher | Taylor & Francis |
|---|---|
| Reference style | Author–year (Chicago, T&F) Author–year — (Smith, 2023) in the text Smith, Ada, Ben Jones, and Cara Lee. 2023. "A Representative Article Title." Mathematische Operationsforschung und Statistik Series Optimization 12 (3): 45–58.
Formats any DOI in Mathematische Operationsforschung und Statistik Series Optimization style. No sign-up. |
| Publishes research in | Advanced Optimization Algorithms Research Optimization and Variational Analysis Physics and Engineering Research Articles Advanced Queuing Theory Analysis Risk and Portfolio Optimization |
| ISSN | 0323-3898 |
| h-index | 21 |
| i10-index | 49 |
| Total citations | 2,240 |
| Top institutions publishing here | TU Bergakademie Freiberg |
| Journal website | www.tandfonline.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
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Sequential quadratic programming (SQP) methods are widely used for solving practical optimization problems, especially in structural mechanics. The general structure of SQP methods is briefly introduced and it is shown how these methods can be adapted to distributed computing. However, SQP methods are sensitive subject to errors in function and gradient evaluations. Typically they break…
The existence of equivalent scalar problems for Pareto optimizations over arbitrary cones is studied in locally convex spaces with emphasis on the geometric relationships between various cones. Applications to non-linear programming and convex programming are given.
If a partial ordering or preordering induced by a cone D defines a multi objective optimization problem, then scalarizing functionals for this problem shall posses two basic properties. D – monotonicity and D e approximation. Several ways of constructing functionals with these properties are discussed in the paper.
Under suitable convexity and integrability assumptions, for the stochastic programming problem with recourse statements are proved very easily, which have been shown until now only for stochastic linear programming. In particular, this includes lower bounds for approximations using discrete random vectors. Until now unpublished, even for the linear ease, are error bounds, which are proved…
Let m denote the infimum of the Integral of a function q w r t all probability measures with given marginals. The determination of m is of interest for a series of stochastic problems. In the present paper we prove a duality theorem for the determination of m and give some examples for its application.…
