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In a classical problem in scheduling, one has $n$ unit size jobs with a precedence order and the goal is to find a schedule of those jobs on $m$ identical machines as to minimize the makespan. It is one of the remaining four open problems…

Data Structures and Algorithms · Computer Science 2018-02-19 Elaine Levey , Thomas Rothvoss

Given a set $P$ of $n$ weighted points and a set $S$ of $m$ disks in the plane, the hitting set problem is to compute a subset $P'$ of points of $P$ such that each disk contains at least one point of $P'$ and the total weight of all points…

Computational Geometry · Computer Science 2023-05-17 Gang Liu , Haitao Wang

To analyze the worst-case running time of branching algorithms, the majority of work in exponential time algorithms focuses on designing complicated branching rules over developing better analysis methods for simple algorithms. In the…

Data Structures and Algorithms · Computer Science 2024-07-02 Katie Clinch , Serge Gaspers , Zixu He , Abdallah Saffidine , Tiankuang Zhang

We consider the classical scheduling problem on parallel identical machines to minimize the makespan, and achieve the following results under the Exponential Time Hypothesis (ETH) 1. The scheduling problem on a constant number $m$ of…

Computational Complexity · Computer Science 2013-10-02 Lin Chen , Klaus Jansen , Guochuan Zhang

We propose an exact polynomial algorithm for a resource allocation problem with convex costs and constraints on partial sums of resource consumptions, in the presence of either continuous or integer variables. No assumption of strict…

Data Structures and Algorithms · Computer Science 2014-04-29 Thibaut Vidal , Patrick Jaillet , Nelson Maculan

We study stochastic combinatorial optimization problems where the objective is to minimize the expected maximum load (a.k.a.\ the makespan). In this framework, we have a set of $n$ tasks and $m$ resources, where each task $j$ uses some…

Data Structures and Algorithms · Computer Science 2021-06-25 Anupam Gupta , Amit Kumar , Viswanath Nagarajan , Xiangkun Shen

Machine scheduling problems involving conflict jobs can be seen as a constrained version of the classical scheduling problem, in which some jobs are conflict in the sense that they cannot be proceeded simultaneously on different machines.…

Data Structures and Algorithms · Computer Science 2021-02-12 Minh Hoàng Hà , Dinh Quy Ta , Trung Thanh Nguyen

This paper considers the online machine minimization problem, a basic real time scheduling problem. The setting for this problem consists of n jobs that arrive over time, where each job has a deadline by which it must be completed. The goal…

Data Structures and Algorithms · Computer Science 2018-01-31 Sungjin Im , Benjamin Moseley , Kirk Pruhs , Clifford Stein

As the gap between compute and I/O performance tends to grow, modern High-Performance Computing (HPC) architectures include a new resource type: an intermediate persistent fast memory layer, called burst buffers. This is just one of many…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-01 Adrian Naruszko , Bartłomiej Przybylski , Krzysztof Rzadca

Fashion discounters face the problem of ordering the right amount of pieces in each size of a product. The product is ordered in pre-packs containing a certain size-mix of a product. For this so-called lot-type design problem, a stochastic…

Optimization and Control · Mathematics 2016-03-26 Miriam Kießling , Tobias Kreisel , Sascha Kurz , Jörg Rambau

The length-constrained cycle partition problem (LCCP) is a graph optimization problem in which a set of nodes must be partitioned into a minimum number of cycles. Every node is associated with a critical time and the length of every cycle…

Optimization and Control · Mathematics 2024-02-05 Mohammed Ghannam , Gioni Mexi , Edward Lam , Ambros Gleixner

We introduce a new approach for the numerical pricing of American options. The main idea is to choose a finite number of suitable excessive functions (randomly) and to find the smallest majorant of the gain function in the span of these…

Computational Finance · Quantitative Finance 2013-10-17 Sören Christensen

Many learning algorithms are formulated in terms of finding model parameters which minimize a data-fitting loss function plus a regularizer. When the regularizer involves the l0 pseudo-norm, the resulting regularization path consists of a…

Machine Learning · Computer Science 2020-03-06 Toby Hocking , Joseph Vargovich

We consider the problem of designing piecewise affine policies for two-stage adjustable robust linear optimization problems under right-hand side uncertainty. It is well known that a piecewise affine policy is optimal although the number of…

Optimization and Control · Mathematics 2018-01-23 Aharon Ben-Tal , Omar El Housni , Vineet Goyal

We provide polynomial-time approximately optimal Bayesian mechanisms for makespan minimization on unrelated machines as well as for max-min fair allocations of indivisible goods, with approximation factors of $2$ and $\min\{m-k+1,…

Computer Science and Game Theory · Computer Science 2014-05-26 Constantinos Daskalakis , S. Matthew Weinberg

We analyze the bit complexity of efficient algorithms for fundamental optimization problems, such as linear regression, $p$-norm regression, and linear programming (LP). State-of-the-art algorithms are iterative, and in terms of the number…

Data Structures and Algorithms · Computer Science 2023-04-06 Mehrdad Ghadiri , Richard Peng , Santosh S. Vempala

The exact complexity of geometric cuts and bisections is the longstanding open problem including even the dimension one. In this paper, we resolve this problem for dimension one (the real line) by designing an exact polynomial time…

Data Structures and Algorithms · Computer Science 2012-07-05 Marek Karpinski , Andrzej Lingas , Dzmitry Sledneu

We consider the problem of detecting change-points in univariate time series by fitting a continuous piecewise linear signal using the residual sum of squares. Values of the inferred signal at slope breaks are restricted to a finite set of…

Computation · Statistics 2022-04-08 Vincent Runge , Marco Pascucci , Nicolas Deschamps de Boishebert

Numerically solving multi-marginal optimal transport (MMOT) problems is computationally prohibitive, even for moderate-scale instances involving $l\ge4$ marginals with support sizes of $N\ge1000$. The cost in MMOT is represented as a tensor…

Numerical Analysis · Mathematics 2026-04-03 Chunhui Chen , Jing Chen , Baojia Luo , Shi Jin , Hao Wu

The interval scheduling problem is one variant of the scheduling problem. In this paper, we propose a novel variant of the interval scheduling problem, whose definition is as follows: given jobs are specified by their {\em release times},…

Data Structures and Algorithms · Computer Science 2018-05-16 Koji M. Kobayashi