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Deep neural networks training jobs and other iterative computations frequently include checkpoints where jobs can be canceled based on the current value of monitored metrics. While most of existing results focus on the performance of all…

Performance · Computer Science 2022-09-30 Yuan Yao , Marco Paolieri , Leana Golubchik

We introduce the method of using an annealing genetic algorithm to the numerically complex problem of looking for quantum logic gates which simultaneously have highest fidelity and highest success probability. We first use the linear…

Quantum Physics · Physics 2007-09-05 Zhanghan Wu , Sean D. Huver , Dmitry Uskov , Hwang Lee , Jonathan P. Dowling

We examine a standard factory scheduling problem with stochastic processing and setup times, minimizing the expectation of the weighted number of tardy jobs. Because the costs of operators in the schedule are stochastic and sequence…

Artificial Intelligence · Computer Science 2013-02-18 Peter R. Wurman , Michael P. Wellman

Traffic congestion has lead to an increasing emphasis on management measures for a more efficient utilization of existing infrastructure. In this context, this paper proposes a novel framework that integrates real-time optimization of…

Systems and Control · Electrical Eng. & Systems 2024-12-20 Samarth Gupta , Ravi Seshadri , Bilge Atasoy , A. Arun Prakash , Francisco Pereira , Gary Tan , Moshe Ben-Akiva

We propose throughput and cost optimal job scheduling algorithms in cloud computing platforms offering Infrastructure as a Service. We first consider online migration and propose job scheduling algorithms to minimize job migration and…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-07 Haritha K , Chandramani Singh

The aim of this research is twofold: Firstly, to model and solve a complex nurse scheduling problem with an integer programming formulation and evolutionary algorithms. Secondly, to detail a novel statistical method of comparing and hence…

Neural and Evolutionary Computing · Computer Science 2010-07-05 Uwe Aickelin , Paul White

We study scheduling of computation tasks across n workers in a large scale distributed learning problem with the help of a master. Computation and communication delays are assumed to be random, and redundant computations are assigned to…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-08 Mohammad Mohammadi Amiri , Deniz Gunduz

There is an abundance of prior research on the optimization of production systems, but there is a research gap when it comes to optimizing which components should be included in a design, and how they should be connected. To overcome this…

Neural and Evolutionary Computing · Computer Science 2024-02-05 N. Paape , J. A. W. M. van Eekelen , M. A. Reniers

Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each persons assignment. Unlike our previous work of using genetic…

Neural and Evolutionary Computing · Computer Science 2010-07-05 Jingpeng Li , Uwe Aickelin

In this paper we analyze the problem of optimal task scheduling for data centers. Given the available resources and tasks, we propose a fast distributed iterative algorithm which operates over a large scale network of nodes and allows each…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-04-08 Apostolos I. Rikos , Andreas Grammenos , Evangelia Kalyvianaki , Christoforos N. Hadjicostis , Themistoklis Charalambous , Karl H. Johansson

In this paper, we aim to obtain the optimal delay-power tradeoff and the corresponding optimal scheduling policy for an arbitrary i.i.d. arrival process and adaptive transmissions. The number of backlogged packets at the transmitter is…

Information Theory · Computer Science 2017-11-01 Xiang Chen , Wei Chen , Joohyun Lee , Ness B. Shroff

This paper deals with the resolution of combinatorial optimization problems, particularly those concerning the maritime transport scheduling. We are interested in the management platforms in a river port and more specifically in container…

Neural and Evolutionary Computing · Computer Science 2013-06-04 R. Kammarti , I. Ayachi , M. Ksouri , P. Borne

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

We consider the setting where a master wants to run a distributed stochastic gradient descent (SGD) algorithm on $n$ workers each having a subset of the data. Distributed SGD may suffer from the effect of stragglers, i.e., slow or…

Machine Learning · Computer Science 2023-10-18 Serge Kas Hanna , Rawad Bitar , Parimal Parag , Venkat Dasari , Salim El Rouayheb

The demand for stringent interactive quality-of-service has intensified in both mobile edge computing (MEC) and cloud systems, driven by the imperative to improve user experiences. As a result, the processing of computation-intensive tasks…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-28 Ngoc Hung Nguyen , Van-Dinh Nguyen , Anh Tuan Nguyen , Nguyen Van Thieu , Hoang Nam Nguyen , Symeon Chatzinotas

The manpower scheduling problem is a kind of critical combinational optimization problem. Researching solutions to scheduling problems can improve the efficiency of companies, hospitals, and other work units. This paper proposes a new model…

Machine Learning · Computer Science 2021-05-11 Tianyu Liu , Lingyu Zhang

In the paper, the new approach to the scheduling problem are described. The approach deals with the problem of planning the cyclic production and proposes to consider such scheduling problem as the cyclic job-shop problem of the order k,…

Neural and Evolutionary Computing · Computer Science 2020-06-22 Pavel Matrenin , Vadim Manusov

We present a number of novel algorithms, based on mathematical optimization formulations, in order to solve a homogeneous multiprocessor scheduling problem, while minimizing the total energy consumption. In particular, for a system with a…

Operating Systems · Computer Science 2015-11-13 Mason Thammawichai , Eric C. Kerrigan

In railway operations, a timetable is established to determine the departure and arrival times for the trains or other rolling stock at the different stations or relevant points inside the rail network or a subset of this network. The…

Artificial Intelligence · Computer Science 2014-11-26 Diego Arenas , Remy Chevirer , Said Hanafi , Joaquin Rodriguez

Workforce scheduling in the healthcare sector is a significant operational challenge, characterized by fluctuating patient loads, diverse clinical skills, and the critical need to control labor costs while upholding high standards of…

Artificial Intelligence · Computer Science 2025-08-29 Vipul Patel , Anirudh Deodhar , Dagnachew Birru
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