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We consider the classical scheduling problem on a single machine, on which we need to schedule sequentially $n$ given jobs. Every job $j$ has a processing time $p_j$ and a priority weight $w_j$, and for a given schedule a completion time…

Data Structures and Algorithms · Computer Science 2015-12-22 Nikhil Bansal , Christoph Dürr , Nguyen Kim Thang , Óscar C. Vásquez

We study shared processor scheduling of $\textit{multiprocessor}$ weighted jobs where each job can be executed on its private processor and simultaneously on possibly $\textit{many}$ processors shared by all jobs in order to reduce their…

Discrete Mathematics · Computer Science 2024-01-26 Dariusz Dereniowski , Wieslaw Kubiak

We consider non-preemptive scheduling of MapReduce jobs with multiple tasks in the practical scenario where each job requires several map-reduce rounds. We seek to minimize the average weighted completion time and consider scheduling on…

Data Structures and Algorithms · Computer Science 2016-02-18 Dimitris Fotakis , Ioannis Milis , Orestis Papadigenopoulos , Vasilis Vassalos , Georgios Zois

We study pseudo-polynomial time algorithms for the fundamental \emph{0-1 Knapsack} problem. In terms of $n$ and $w_{\max}$, previous algorithms for 0-1 Knapsack have cubic time complexities: $O(n^2w_{\max})$ (Bellman 1957), $O(nw_{\max}^2)$…

Data Structures and Algorithms · Computer Science 2023-08-10 Ce Jin

We consider the problem of scheduling $n$ precedence-constrained jobs on $m$ uniformly-related machines in the presence of an arbitrary, fixed communication delay $\rho$. We consider a model that allows job duplication, i.e. processing of…

Data Structures and Algorithms · Computer Science 2020-04-24 Biswaroop Maiti , Rajmohan Rajaraman , David Stalfa , Zoya Svitkina , Aravindan Vijayaraghavan

An important area of research in exact algorithms is to solve Subset-Sum-type problems faster than meet-in-middle. In this paper we study Pigeonhole Equal Sums, a total search problem proposed by Papadimitriou (1994): given $n$ positive…

Data Structures and Algorithms · Computer Science 2024-03-29 Ce Jin , Hongxun Wu

The subset sum problem is known to be an NP-hard problem in the field of computer science with the fastest known approach having a run-time complexity of $O(2^{0.3113n})$. A modified version of this problem is known as the perfect sum…

Data Structures and Algorithms · Computer Science 2022-11-29 Kristof Pusztai

In this paper, we consider an approach to the parallelizing of the algorithms realizing the modified probability changigng method with adaptation and partial rollback procedure for constrained pseudo-Boolean optimization problems. Existing…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-09-03 Lev Kazakovtsev

Load balance is important for MapReduce to reduce job duration, increase parallel efficiency, etc. Previous work focuses on coarse-grained scheduling. This study concerns fine-grained scheduling on MapReduce operations. Each operation…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-04-15 Liya Fan , Bo Gao , Xi Sun , Fa Zhang , Zhiyong Liu

The subset sum problem (SSP) can be briefly stated as: given a target integer $E$ and a set $A$ containing $n$ positive integer $a_j$, find a subset of $A$ summing to $E$. The \textit{density} $d$ of an SSP instance is defined by the ratio…

Data Structures and Algorithms · Computer Science 2008-06-23 Changlin Wan , Zhongzhi Shi

In this work, we study the classic submodular maximization problem under knapsack constraints and beyond. We first present an $(7/16-\varepsilon)$-approximate algorithm for single knapsack constraint, which requires…

Data Structures and Algorithms · Computer Science 2020-12-22 Wenxin Li

We consider fast algorithms for monotone submodular maximization subject to a matroid constraint. We assume that the matroid is given as input in an explicit form, and the goal is to obtain the best possible running times for important…

Data Structures and Algorithms · Computer Science 2018-11-20 Alina Ene , Huy L. Nguyen

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

Interval scheduling is a basic problem in the theory of algorithms and a classical task in combinatorial optimization. We develop a set of techniques for partitioning and grouping jobs based on their starting and ending times, that enable…

Data Structures and Algorithms · Computer Science 2023-02-27 Spencer Compton , Slobodan Mitrović , Ronitt Rubinfeld

We consider the classical online scheduling problem P||C_{max} in which jobs are released over list and provide a nearly optimal online algorithm. More precisely, an online algorithm whose competitive ratio is at most (1+\epsilon) times…

Data Structures and Algorithms · Computer Science 2013-02-19 Lin Chen , Deshi Ye , Guochuan Zhang

Assuming that P is not equal to NP, the worst-case run time of any algorithm solving an NP-complete problem must be super-polynomial. But what is the fastest run time we can get? Before one can even hope to approach this question, a more…

Data Structures and Algorithms · Computer Science 2026-01-09 Jesper Nederlof

This paper studies the scheduling of jobs of different families on parallel machines with qualification constraints. Originating from semiconductor manufacturing, this constraint imposes a time threshold between the execution of two jobs of…

Artificial Intelligence · Computer Science 2020-11-23 Margaux Nattaf , Arnaud Malapert

We consider scheduling problems for unit jobs with release times, where the number or size of the gaps in the schedule is taken into consideration, either in the objective function or as a constraint. Except for a few papers on energy…

Data Structures and Algorithms · Computer Science 2020-07-21 Marek Chrobak , Mordecai Golin , Tak-Wah Lam , Dorian Nogneng

We consider several combinatorial optimization problems which combine the classic shop scheduling problems, namely open shop scheduling or job shop scheduling, and the shortest path problem. The objective of the obtained problem is to…

Data Structures and Algorithms · Computer Science 2013-09-03 Kameng Nip , Zhenbo Wang , Wenxun Xing

We study the problem of preemptive scheduling of n equal-length jobs with given release times on m identical parallel machines. The objective is to minimize the average flow time. Recently, Brucker and Kravchenko proved that the optimal…

Data Structures and Algorithms · Computer Science 2007-05-23 Philippe Baptiste , Marek Chrobak , Christoph Durr , Francis Sourd