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Stochastic approximation techniques have been used in various contexts in data science. We propose a stochastic version of the forward-backward algorithm for minimizing the sum of two convex functions, one of which is not necessarily…

Optimization and Control · Mathematics 2016-02-26 Patrick L. Combettes , Jean-Christophe Pesquet

The NP-hard scheduling problem P||C_max encompasses a set of tasks with known execution time which must be mapped to a set of identical machines such that the overall completion time is minimized. In this work, we improve existing…

Data Structures and Algorithms · Computer Science 2024-10-22 Matthew Akram , Nikolai Maas , Peter Sanders , Dominik Schreiber

One of the most important open problems in machine scheduling is the problem of scheduling a set of jobs on unrelated machines to minimize the makespan. The best known approximation algorithm for this problem guarantees an approximation…

Discrete Mathematics · Computer Science 2015-03-17 José Verschae , Andreas Wiese

We investigate two new optimization problems -- minimizing a submodular function subject to a submodular lower bound constraint (submodular cover) and maximizing a submodular function subject to a submodular upper bound constraint…

Data Structures and Algorithms · Computer Science 2013-11-12 Rishabh Iyer , Jeff Bilmes

In contrast with many other convex optimization classes, state-of-the-art semidefinite programming solvers are yet unable to efficiently solve large scale instances. This work aims to reduce this scalability gap by proposing a novel…

Optimization and Control · Mathematics 2018-12-20 Mario Souto , Joaquim D. Garcia , Alvaro Veiga

A prominent problem in scheduling theory is the weighted flow time problem on one machine. We are given a machine and a set of jobs, each of them characterized by a processing time, a release time, and a weight. The goal is to find a…

Data Structures and Algorithms · Computer Science 2023-08-14 Alexander Armbruster , Lars Rohwedder , Andreas Wiese

The Jobs shop Scheduling Problem (JSP) is a canonical combinatorial optimization problem that is routinely solved for a variety of industrial purposes. It models the optimal scheduling of multiple sequences of tasks, each under a fixed…

Machine Learning · Computer Science 2021-10-14 James Kotary , Ferdinando Fioretto , Pascal Van Hentenryck

We present a primal-dual algorithmic framework to obtain approximate solutions to a prototypical constrained convex optimization problem, and rigorously characterize how common structural assumptions affect the numerical efficiency. Our…

Optimization and Control · Mathematics 2015-03-04 Quoc Tran-Dinh , Volkan Cevher

The subject of this paper is the time complexity of approximating Knapsack, Subset Sum, Partition, and some other related problems. The main result is an $\widetilde{O}(n+1/\varepsilon^{5/3})$ time randomized FPTAS for Partition, which is…

Data Structures and Algorithms · Computer Science 2019-05-07 Marcin Mucha , Karol Węgrzycki , Michał Włodarczyk

In this paper we study the classical problem of throughput maximization. In this problem we have a collection $J$ of $n$ jobs, each having a release time $r_j$, deadline $d_j$, and processing time $p_j$. They have to be scheduled…

Data Structures and Algorithms · Computer Science 2020-02-14 Dylan Hyatt-Denesik , Mirmahdi Rahgoshay , Mohammad R. Salavatipour

In this paper, we consider four single-machine scheduling problems with release times, with the aim of minimizing the maximum lateness. In the first problem we have a common deadline for all the jobs. The second problem looks for the Pareto…

Data Structures and Algorithms · Computer Science 2017-08-18 Imed Kacem , Hans Kellerer

A mixed shop is a manufacturing infrastructure designed to process a mixture of a set of flow-shop jobs and a set of open-shop jobs. Mixed shops are in general much more complex to schedule than flow-shops and open-shops, and have been…

Data Structures and Algorithms · Computer Science 2018-09-18 Longcheng Liu , Yong Chen , Jianming Dong , Randy Goebel , Guohui Lin , Yue Luo , Guanqun Ni , Bing Su , An Zhang

We study the classical scheduling problem of minimizing the makespan of a set of unit size jobs with precedence constraints on parallel identical machines. Research on the problem dates back to the landmark paper by Graham from 1966 who…

Data Structures and Algorithms · Computer Science 2025-01-17 Syamantak Das , Andreas Wiese

Constrained submodular maximization problems encompass a wide variety of applications, including personalized recommendation, team formation, and revenue maximization via viral marketing. The massive instances occurring in modern day…

Data Structures and Algorithms · Computer Science 2024-02-20 Georgios Amanatidis , Federico Fusco , Philip Lazos , Stefano Leonardi , Rebecca Reiffenhäuser

In the moldable job scheduling problem one has to assign a set of $n$ jobs to $m$ machines, in order to minimize the time it takes to process all jobs. Each job is moldable, so it can be assigned not only to one but any number of the equal…

Data Structures and Algorithms · Computer Science 2023-03-03 Kilian Grage , Klaus Jansen , Felix Ohnesorge

We address long-standing open questions raised by Williamson, Goemans, Vazirani and Mihail pertaining to the design of approximation algorithms for problems in network design via the primal-dual method (Combinatorica 15(3):435-454, 1995).…

Data Structures and Algorithms · Computer Science 2024-01-10 Ishan Bansal , Joseph Cheriyan , Logan Grout , Sharat Ibrahimpur

In the paper we consider the problem of scheduling $n$ identical jobs on 4 uniform machines with speeds $s_1 \geq s_2 \geq s_3 \geq s_4,$ respectively. Our aim is to find a schedule with a minimum possible length. We assume that jobs are…

Data Structures and Algorithms · Computer Science 2016-02-08 H. Furmanczyk , M. Kubale

In real-time systems, in addition to the functional correctness recurrent tasks must fulfill timing constraints to ensure the correct behavior of the system. Partitioned scheduling is widely used in real-time systems, i.e., the tasks are…

Data Structures and Algorithms · Computer Science 2018-09-13 Jian-Jia Chen , Nikhil Bansal , Samarjit Chakraborty , Georg von der Brüggen

We study a class of combinatorial scheduling problems characterized by a particular type of constraint often associated with electrical power or gas energy. This constraint appears in several practical applications and is expressed as a sum…

Data Structures and Algorithms · Computer Science 2023-12-27 Trung Thanh Nguyen , Khaled Elbassioni , Areg Karapetyan , Majid Khonji

We study the problem of non-preemptively scheduling $n$ jobs, each job $j$ with a release time $t_j$, a deadline $d_j$, and a processing time $p_j$, on $m$ parallel identical machines. Cieliebak et al. (2004) considered the two constraints…

Data Structures and Algorithms · Computer Science 2017-05-25 René van Bevern , Rolf Niedermeier , Ondřej Suchý
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