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We consider the uniform parallel machines scheduling problem in the context of optimistic bilevel optimization, where two speed options are considered. In this scenario, the leader aims to minimize the weighted number of tardy jobs, while…

Optimization and Control · Mathematics 2026-03-06 Quentin Schau , Olivier Ploton , Vincent T'kindt , Han Hoogeveen , Federico Della Croce , Jippe Hoogeveen

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

This paper studies a scheduling problem in a parallel machine setting, where each machine must adhere to a predetermined fixed order for processing the jobs. Given $n$ jobs, each with processing times and deadlines, we aim to minimize the…

Data Structures and Algorithms · Computer Science 2025-05-16 Andre Berger , Arman Rouhani , Marc Schröder

Allocating conflicting jobs among individuals while respecting a budget constraint for each individual is an optimization problem that arises in various real-world scenarios. In this paper, we consider the situation where each individual…

Data Structures and Algorithms · Computer Science 2024-02-06 Sushmita Gupta , Pallavi Jain , A. Mohanapriya , Vikash Tripathi

While almost all existing works which optimally solve just-in-time scheduling problems propose dedicated algorithmic approaches, we propose in this work mixed integer formulations. We consider a single machine scheduling problem that aims…

Data Structures and Algorithms · Computer Science 2021-02-15 Anne-Elisabeth Falq , Pierre Fouilhoux , Safia Kedad-Sidhoum

Most supervised machine learning tasks are subject to irreducible prediction errors. Probabilistic predictive models address this limitation by providing probability distributions that represent a belief over plausible targets, rather than…

Machine Learning · Statistics 2022-10-25 David Widmann , Fredrik Lindsten , Dave Zachariah

Nowadays hybrid evolutionary algorithms, i.e, heuristic search algorithms combining several mutation operators some of which are meant to implement stochastically a well known technique designed for the specific problem in question while…

Neural and Evolutionary Computing · Computer Science 2014-04-23 Boris Mitavskiy , Jun He

In the context of decision making under explorable uncertainty, scheduling with testing is a powerful technique used in the management of computer systems to improve performance via better job-dispatching decisions. Upon job arrival, a…

Performance · Computer Science 2025-02-13 Jonatha Anselmi , Josu Doncel

Logic-Based Benders Decomposition (LBBD) and its Branch-and-Cut variant, namely Branch-and-Check, enjoy an extensive applicability on a broad variety of problems, including scheduling. Although LBBD offers problem-specific cuts to impose…

Optimization and Control · Mathematics 2025-04-02 Ioannis Avgerinos , Ioannis Mourtos , Stavros Vatikiotis , Georgios Zois

This paper considers parallel machine scheduling with incompatibilities between jobs. The jobs form a graph and no two jobs connected by an edge are allowed to be assigned to the same machine. In particular, we study the case where the…

Computational Complexity · Computer Science 2021-03-16 Klaus Jansen , Alexandra Lassota , Marten Maack , Tytus Pikies

This paper studies the bicriteria problem of scheduling $n$ jobs on a serial-batch machine to minimize makespan and maximum cost simultaneously. A serial-batch machine can process up to $b$ jobs as a batch, where $b$ is known as the batch…

Data Structures and Algorithms · Computer Science 2025-04-01 Shuguang Li , Zhenxin Wen , Jing Wei

This paper focuses on managing the cost of deliberation before action. In many problems, the overall quality of the solution reflects costs incurred and resources consumed in deliberation as well as the cost and benefit of execution, when…

Artificial Intelligence · Computer Science 2013-04-05 David Einav , Michael R. Fehling

In this work, we propose a mean-squared error-based risk that enables the comparison and optimization of estimators of squared calibration errors in practical settings. Improving the calibration of classifiers is crucial for enhancing the…

Machine Learning · Computer Science 2025-02-24 Sebastian G. Gruber , Francis Bach

The problem of high-dimensional path-dependent optimal stopping (OS) is important to multiple academic communities and applications. Modern OS tasks often have a large number of decision epochs, and complicated non-Markovian dynamics,…

Probability · Mathematics 2024-05-16 David A. Goldberg , Yilun Chen

In this paper we address the problem of designing an interruptible system in a setting in which $n$ problem instances, all equally important, must be solved concurrently. The system involves scheduling executions of contract algorithms…

Data Structures and Algorithms · Computer Science 2018-10-29 Spyros Angelopoulos , Alejandro Lopez-Ortiz

We consider the following shared-resource scheduling problem: Given a set of jobs $J$, for each $j\in J$ we must schedule a job-specific processing volume of $v_j>0$. A total resource of $1$ is available at any time. Jobs have a resource…

Data Structures and Algorithms · Computer Science 2023-10-11 Christoph Damerius , Peter Kling , Florian Schneider

Consider a multi-class labelling problem, where the labels can take values in $[k]$, and a predictor predicts a distribution over the labels. In this work, we study the following foundational question: Are there notions of multi-class…

Machine Learning · Computer Science 2024-06-11 Parikshit Gopalan , Lunjia Hu , Guy N. Rothblum

Generalizing many well-known and natural scheduling problems, scheduling with job-specific cost functions has gained a lot of attention recently. In this setting, each job incurs a cost depending on its completion time, given by a private…

Data Structures and Algorithms · Computer Science 2014-03-07 Wiebke Höhn , Julián Mestre , Andreas Wiese

This paper proposes a thought experiment to search for efficient bounded algorithms of NPC problems by machine enumeration. The key contributions are: -- On Universal Turing Machines, a program's time complexity should be characterized as:…

Computational Complexity · Computer Science 2012-10-09 YuQian Zhou

We investigate the scheduling of $n$ jobs divided into $c$ classes on $m$ identical parallel machines. For every class there is a setup time which is required whenever a machine switches from the processing of one class to another class.…

Data Structures and Algorithms · Computer Science 2019-05-02 Max A. Deppert , Klaus Jansen