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The Oven Scheduling Problem (OSP) is a new parallel batch scheduling problem that arises in the area of electronic component manufacturing. Jobs need to be scheduled to one of several ovens and may be processed simultaneously in one batch…

Artificial Intelligence · Computer Science 2022-03-24 Marie-Louise Lackner , Christoph Mrkvicka , Nysret Musliu , Daniel Walkiewicz , Felix Winter

This paper addresses the scheduling problem on two identical parallel machines with a single server in charge of loading and unloading operations of jobs. Each job has to be loaded by the server before being processed on one of the two…

Optimization and Control · Mathematics 2023-06-30 Abdelhak Elidrissi , Rachid Banmansour , Keramat Hasani , Frank Werner

Capacity sharing networks are typical heterogeneous communication networks widely applied in information and communications technology (ICT) field. In such networks, resources like bandwidth, spectrum, computation and storage are shared…

Optimization and Control · Mathematics 2024-12-03 Kaixiang Hu , Feilong Huang , Caixia Kou

Dial-a-Ride problems have been proposed to model the challenge to consolidate passenger transportation requests with a fleet of shared vehicles. The line-based Dial-a-Ride problem (LiDARP) is a variant where the passengers are transported…

Computational Complexity · Computer Science 2026-05-01 Antonio Lauerbach , Kendra Reiter , Marie Schmidt

A mathematical programming model for a class of single machine family scheduling problem is described in this technical report, with the aim of comparing the performance in solving the scheduling problem by means of mathematical programming…

Optimization and Control · Mathematics 2015-03-03 Davide Giglio

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

Symbolic regression that aims to detect underlying data-driven models has become increasingly important for industrial data analysis. For most existing algorithms such as genetic programming (GP), the convergence speed might be too slow for…

Neural and Evolutionary Computing · Computer Science 2017-10-31 Chen Chen , Changtong Luo , Zonglin Jiang

This paper addresses the problem of fault diagnosis in multistation assembly systems. Fault diagnosis is to identify process faults that cause the excessive dimensional variation of the product using dimensional measurements. For such…

Applications · Statistics 2022-10-31 Jihoon Chung , Bo Shen , Zhenyu , Kong

We consider the problem of partial order production: arrange the elements of an unknown totally ordered set T into a target partially ordered set S, by comparing a minimum number of pairs in T. Special cases include sorting by comparisons,…

Data Structures and Algorithms · Computer Science 2010-05-06 Jean Cardinal , Samuel Fiorini , Gwenaël Joret , Raphaël M. Jungers , J. Ian Munro

Floor planning is an important and difficult task in architecture. When planning office buildings, rooms that belong to the same organisational unit should be placed close to each other. This leads to the following NP-hard mathematical…

Computational Geometry · Computer Science 2021-07-13 Jonathan Klawitter , Felix Klesen , Alexander Wolff

This study presents optimization problems to jointly determine long-term network design, mid-term fleet sizing strategy, and short-term routing and ridesharing matching in shared autonomous vehicle (SAV) systems with pre-booked and…

Optimization and Control · Mathematics 2024-09-19 Riki Kawase

We deal with a challenging scheduling problem on parallel machines with sequence-dependent setup times and release dates from a real-world application of semiconductor work-shop production. There, jobs can only be processed by dedicated…

Artificial Intelligence · Computer Science 2024-11-01 Thomas Eiter , Tobias Geibinger , Nysret Musliu , Johannes Oetsch , Peter Skocovsky , Daria Stepanova

The constant increase in parallelism available on large-scale distributed computers poses major scalability challenges to many scientific applications. A common strategy to improve scalability is to express the algorithm in terms of…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-23 Andrew Garmon , Vinay Ramakrishnaiah , Danny Perez

Long-horizon task and motion planning (TAMP) is notoriously difficult to solve, let alone optimally, due to the tight coupling between the interleaved (discrete) task and (continuous) motion planning phases, where each phase on its own is…

Robotics · Computer Science 2024-04-11 Kai Gao , Zihe Ye , Duo Zhang , Baichuan Huang , Jingjin Yu

In parallel computing, a problem is divided into a set of smaller tasks that are distributed across multiple processing elements. Balancing the load of the processing elements is key to achieving good performance and scalability. If the…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-08-02 Omer Demirel , Ivo F. Sbalzarini

For scheduling in flexible manufacturing system (FMS), many factors should be considered, it is difficult to solve the scheduling problem by satisfying different criteria (production cost, utilization of system, number of movements of part,…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-24 U Yongnam , Ri Taehyong

We investigate the construction and performance of summation-by-parts (SBP) operators, which offer a powerful framework for the systematic development of structure-preserving numerical discretizations of partial differential equations.…

Numerical Analysis · Mathematics 2026-02-12 Jan Glaubitz , Armin Iske , Joshua Lampert , Philipp Öffner

Operator splitting methods have been successfully used in computational sciences, statistics, learning and vision areas to reduce complex problems into a series of simpler subproblems. However, prevalent splitting schemes are mostly…

Computer Vision and Pattern Recognition · Computer Science 2018-05-01 Risheng Liu , Shichao Cheng , Yi He , Xin Fan , Zhongxuan Luo

We study the expected completion time of some recently proposed algorithms for distributed computing which redundantly assign computing tasks to multiple machines in order to tolerate a certain number of machine failures. We analytically…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-08-10 Amir Behrouzi-Far , Emina Soljanin

Applications such as megaregional planning require efficient methods for solving traffic assignment problems (TAPs) on large-scale networks. We propose a decomposition heuristic that generates approximate TAP solutions by partitioning the…

Optimization and Control · Mathematics 2022-06-28 Venktesh Pandey , Priyadarshan N. Patil
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