Split cuts from sparse disjunctions

IF 4.3 1区 数学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING Mathematical Programming Computation Pub Date : 2020-03-04 DOI:10.1007/s12532-020-00180-9
Ricardo Fukasawa, Laurent Poirrier, Shenghao Yang
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来源期刊
Mathematical Programming Computation
Mathematical Programming Computation OPERATIONS RESEARCH & MANAGEMENT SCIENCE-
CiteScore
10.80
自引率
4.80%
发文量
18
期刊介绍: Mathematical Programming Computation (MPC) publishes original research articles advancing the state of the art of practical computation in Mathematical Optimization and closely related fields. Authors are required to submit software source code and data along with their manuscripts (while open-source software is encouraged, it is not required). Where applicable, the review process will aim for verification of reported computational results. Topics of articles include: New algorithmic techniques, with substantial computational testing New applications, with substantial computational testing Innovative software Comparative tests of algorithms Modeling environments Libraries of problem instances Software frameworks or libraries. Among the specific topics covered in MPC are linear programming, convex optimization, nonlinear optimization, stochastic optimization, integer programming, combinatorial optimization, global optimization, network algorithms, and modeling languages. MPC accepts manuscript submission from its own editorial board members in cases in which the identities of the associate editor, reviewers, and technical editor handling the manuscript can remain fully confidential. To be accepted, manuscripts submitted by editorial board members must meet the same quality standards as all other accepted submissions; there is absolutely no special preference or consideration given to such submissions.
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CP-Lib: Benchmark Instances of the Clique Partitioning Problem Self-adaptive ADMM for semi-strongly convex problems Domain-Driven Solver (DDS) Version 2.1: a MATLAB-based software package for convex optimization problems in domain-driven form A parallel hub-and-spoke system for large-scale scenario-based optimization under uncertainty Exact methods for discrete Γ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\varGamma }$$\end{document}-robust interd
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