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We consider a basic problem of preemptive scheduling of $n$ non-simultaneously released jobs on a group of $m$ unrelated parallel machines so as to minimize maximum job completion time, the makespan. In the scheduling literature, the…

Data Structures and Algorithms · Computer Science 2022-05-06 Nodari Vakhania

We study the structure of solutions to linear programming formulations for the traveling salesperson problem (TSP). We perform a detailed analysis of the support of the subtour elimination linear programming relaxation, which leads to…

Data Structures and Algorithms · Computer Science 2015-03-27 Matthias Mnich , Tobias Mömke

Many probabilistic inference tasks involve summations over exponentially large sets. Recently, it has been shown that these problems can be reduced to solving a polynomial number of MAP inference queries for a model augmented with randomly…

Artificial Intelligence · Computer Science 2013-09-27 Stefano Ermon , Carla P. Gomes , Ashish Sabharwal , Bart Selman

The interval subset sum problem (ISSP) is a generalization of the well-known subset sum problem. Given a set of intervals $\left\{[a_{i,1},a_{i,2}]\right\}_{i=1}^n$ and a target integer $T,$ the ISSP is to find a set of integers, at most…

Data Structures and Algorithms · Computer Science 2017-04-25 Rui Diao , Ya-Feng Liu , Yu-Hong Dai

A split of a polytope $P$ is a (regular) subdivision with exactly two maximal cells. It turns out that each weight function on the vertices of $P$ admits a unique decomposition as a linear combination of weight functions corresponding to…

Combinatorics · Mathematics 2008-07-02 Sven Herrmann , Michael Joswig

Recently, we proposed a class of inequalities called lifted bilinear cover inequalities, which are second-order cone representable convex inequalities, and are valid for a set described by a separable bilinear constraint together with…

Optimization and Control · Mathematics 2022-08-02 Xiaoyi Gu , Santanu S. Dey , Jean-Philippe P. Richard

Motivated by the need to better understand the properties of sparse cutting-planes used in mixed integer programming solvers, the paper [2] studied the idealized problem of how well a polytope is approximated by the use of sparse valid…

Optimization and Control · Mathematics 2014-12-12 Santanu S. Dey , Andres Iroume , Marco Molinaro

To support large-scale model training, split learning (SL) enables multiple edge devices/servers to share the intensive training workload. However, most existing works on SL focus solely on two-tier model splitting. Moreover, while some…

Networking and Internet Architecture · Computer Science 2025-09-19 Wei Wei , Zheng Lin , Tao Li , Xuanheng Li , Xianhao Chen

We consider basic problems of non-preemptive scheduling on uniformly related machines. For a given schedule, defined by a partition of the jobs into m subsets corresponding to the m machines, C_i denotes the completion time of machine i.…

Data Structures and Algorithms · Computer Science 2015-03-20 Leah Epstein , Asaf Levin

We propose a new method for separating valid inequalities for the epigraph of a function of binary variables. The proposed inequalities are disjunctive cuts defined by disjunctive terms obtained by enumerating a subset $I$ of the binary…

Optimization and Control · Mathematics 2022-07-12 Rui Chen , James Luedtke

This paper discusses the split feasibility problem with polynomials. The sets are semi-algebraic, defined by polynomial inequalities. They can be either convex or nonconvex, either feasible or infeasible. We give semidefinite relaxations…

Optimization and Control · Mathematics 2017-08-01 Jiawang Nie , Jinling Zhao

Epistemic logic programs (ELPs) are a popular generalization of standard Answer Set Programming (ASP) providing means for reasoning over answer sets within the language. This richer formalism comes at the price of higher computational…

Computational Complexity · Computer Science 2020-01-14 Markus Hecher , Michael Morak , Stefan Woltran

The paper considers a split inverse problem involving component equilibrium problems in Hilbert spaces. This problem therefore is called the split equilibrium problem (SEP). It is known that almost solution methods for solving problem (SEP)…

Optimization and Control · Mathematics 2019-04-17 Dang Van Hieu

We consider the problem of selecting the best variable-value strategy for solving a given problem in constraint programming. We show that the recent Embarrassingly Parallel Search method (EPS) can be used for this purpose. EPS proposes to…

Artificial Intelligence · Computer Science 2016-04-25 Anthony Palmieri , Jean-Charles Régin , Pierre Schaus

We propose a prototypical Split Inverse Problem (SIP) and a new variational problem, called the Split Variational Inequality Problem (SVIP), which is a SIP. It entails finding a solution of one inverse problem (e.g., a Variational…

Optimization and Control · Mathematics 2011-08-11 Yair Censor , Aviv Gibali , Simeon Reich

Goemans and Rothvoss (SODA'14) gave a framework for solving problems which can be described as finding a point in int$.$cone$(P\cap\mathbb{Z}^N)\cap Q$, where $P,Q\subset\mathbb{R}^N$ are (bounded) polyhedra. The running time for solving…

Data Structures and Algorithms · Computer Science 2025-02-03 Klaus Jansen , Kai Kahler , Esther Zwanger

We study the perfect matching reconfiguration problem: Given two perfect matchings of a graph, is there a sequence of flip operations that transforms one into the other? Here, a flip operation exchanges the edges in an alternating cycle of…

Data Structures and Algorithms · Computer Science 2019-04-15 Marthe Bonamy , Nicolas Bousquet , Marc Heinrich , Takehiro Ito , Yusuke Kobayashi , Arnaud Mary , Moritz Mühlenthaler , Kunihiro Wasa

In this paper, we develop a new formulation of changeover constraints for mixed integer programming problem (MIP) that emerges in solving a short-term production scheduling problem. The new model requires fewer constraints than the original…

Optimization and Control · Mathematics 2014-08-28 Pavel A. Borisovsky , Anton V. Eremeev , Josef Kallrath

Semidefinite programs (SDP) are one of the most versatile frameworks in numerical optimization, serving as generalizations of many conic programs and as relaxations of NP-hard combinatorial problems. Their main drawback is their…

Optimization and Control · Mathematics 2022-02-28 Biel Roig-Solvas , Mario Sznaier

It is well known that selecting a good Mixed Integer Programming (MIP) formulation is crucial for an effective solution with state-of-the art solvers. While best practices and guidelines for constructing good formulations abound, there is…

Optimization and Control · Mathematics 2017-05-23 Juan Pablo Vielma