Journal Information

Mathematical Methods of Operations Research

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Impact Factor:
1.2
Publisher:
Springer
ISSN:
1432-2994
Viewed:
15811
Tracked:
0

Call For Papers

Mathematical Methods of Operations Research is an academic journal published by Springer. (ISSN 1432-2994, impact factor 1.2).

Aims and scope This peer reviewed journal publishes original and high-quality articles on important mathematical and computational aspects of operations research, in particular in the areas of continuous and discrete mathematical optimization, stochastics, and game theory. Theoretically oriented papers are supposed to include explicit motivations of assumptions and results, while application oriented papers need to contain substantial mathematical contributions. Suggestions for algorithms should be accompanied with numerical evidence for their superiority over state-of-the-art methods. Articles must be of interest for a large audience in operations research, written in clear and correct English, and typeset in LaTeX. A special section contains invited tutorial papers on advanced mathematical or computational aspects of operations research, aiming at making such methodologies accessible for a wider audience. All papers are refereed. The emphasis is on originality, quality, and importance. Officially cited as: Math Meth Oper Res Jointly sponsored by Gesellschaft fuer Operations Research - The German OR Society Nederlands Genootschap voor Besliskunde - The Dutch OR Society
Last updated by Dou Sun in

Special Issues

Special Issue on Relaxation Methods in Optimization Submission Date: 2026-07-01 The idea of relaxation is one of the common themes across several branches of both discrete and continuous optimization. Typical examples include replacing nonconvex by convex, discrete by continuous or underdetermined by regularized problems. In a broad perspective, relaxation often enables the theoretical treatment of an optimization problem as well as the design of efficient algorithms for its numerical solution. Thus, relaxation methods are one of the key principles in mathematical optimization. The goal of this special issue is to gather recent results and developments on several aspects of relaxation methods, including theory, methodologies and applications of · Linear relaxations · Quadratic relaxations · Second-order cone relaxations · Semidefinite relxations · Conic relaxations · Convex relaxation · Continuous relaxation · Regularization · Relaxation hierarchies · Strenthening relaxations. Submission Please submit manuscripts through the Springer online system and choose the Special Issue. Submission of a manuscript implies that the work described has not been published before; that it is not under consideration for publication anywhere else; that its publication has been approved by all co-authors, if any, as well as by the responsible authorities – tacitly or explicitly – at the institute where the work has been carried out. The publisher will not be held legally responsible should there be any claims for compensation. The journal imposes no hard limits on the paper length as long as the content is important. A paper whose length is about 20 pages in journal format is appreciated. Submissions that exceed 40 pages in journal format (including illustrations and references) should however be accompanied by a short justification as to why a briefer discussion is not possible. Full author instructions may be found at http://www.springer.com/186/submission-guidelines. Any questions related to this special issue should be sent to: Elisabeth Gaar, University of Augsburg, elisabeth.gaar@uni-a.de. André Uschmajew, University of Augsburg, andre.uschmajew@uni-a.de. https://link.springer.com/collections/adbchhgcfg
Last updated by Dou Sun in

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