A Publication of the Mathematical Optimization Society
Mathematical Programming publishes original articles dealing with every aspect of mathematical optimization; that is, everything of direct or indirect use concerning the problem of optimizing a function of many variables, often subject to a set of constraints. This involves theoretical and computational issues as well as application studies. Included, along with the standard topics of linear, nonlinear, integer, conic, stochastic and combinatorial optimization, are techniques for formulating and applying mathematical programming models, convex, nonsmooth and variational analysis, the theory of polyhedra, variational inequalities, and control and game theory viewed from the perspective of mathematical programming. The editorial boards are particularly interested in novel applications of mathematical programming and interfaces with engineering, economics, and computer science. Articles primarily concerned with computational issues such as implementation and testing should in general be submitted to Mathematical Programming Computation.
Mathematical Programming consists of two series. Series A publishes original research articles, expositions and surveys, and reports on computational experimentation and new or innovative practical applications as well as short communications dealing with the above. Issues of Series B each focus on a single subject of current interest to the mathematical programming community. Each issue of Series B has one or more guest editors, who need not be members of the editorial board. An issue may be a collection of original articles, a single research monograph or a selection of papers from a conference.
Full Length Paper
Full Length Paper
Sparse Kalman filtering approaches to realized covariance estimation from high frequency financial data
- Journal Title
- Mathematical Programming
- Volume 1 / 1971 - Volume 176 / 2019
- Print ISSN
- Online ISSN
- Springer Berlin Heidelberg
- Additional Links
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