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The flexible flow shop scheduling problem is an NP-hard problem and it requires significant resolution time to find optimal or even adequate solutions when dealing with large size instances. Thus, this paper proposes a dual island genetic…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-03-27 Jia Luo , Didier El Baz

It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link look ahead search. When a multi-link look ahead search is used, the computational complexity…

Artificial Intelligence · Computer Science 2013-02-08 TongSheng Chu , Yang Xiang

Neural Algorithmic Reasoning is an emerging area of machine learning which seeks to infuse algorithmic computation in neural networks, typically by training neural models to approximate steps of classical algorithms. In this context, much…

Machine Learning · Computer Science 2023-02-10 Danilo Numeroso , Davide Bacciu , Petar Veličković

In this work, we consider a scheduling problem faced by production companies with large electricity consumption. Due to the contract with the electric utility, the production companies are obligated to comply with the total energy…

Data Structures and Algorithms · Computer Science 2018-02-14 István Módos , Přemysl Šůcha , Zdeněk Hanzálek

We propose two parallel state-space exploration algorithms for hybrid systems with the goal of enhancing performance on multi-core shared memory systems. The first is an adaption of the parallel breadth first search in the SPIN model…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-02-27 Amit Gurung , Arup Deka , Ezio Bartocci , Sergiy Bogomolov , Radu Grosu , Rajarshi Ray

Standard approaches to decision-making under uncertainty focus on sequential exploration of the space of decisions. However, \textit{simultaneously} proposing a batch of decisions, which leverages available resources for parallel…

Machine Learning · Statistics 2023-02-07 Jeffrey Chan , Aldo Pacchiano , Nilesh Tripuraneni , Yun S. Song , Peter Bartlett , Michael I. Jordan

This paper studies a bandit optimization problem where the goal is to maximize a function $f(x)$ over $T$ periods for some unknown strongly concave function $f$. We consider a new pairwise comparison oracle, where the decision-maker chooses…

Machine Learning · Computer Science 2025-05-29 Xiangyu Chang , Xi Chen , Yining Wang , Zhiyi Zeng

Parallelization of non-admissible search algorithms such as GBFS poses a challenge because straightforward parallelization can result in search behavior which significantly deviates from sequential search. Previous work proposed PUHF, a…

Data Structures and Algorithms · Computer Science 2025-06-18 Takumi Shimoda , Alex Fukunaga

The anchor words algorithm performs provably efficient topic model inference by finding an approximate convex hull in a high-dimensional word co-occurrence space. However, the existing greedy algorithm often selects poor anchor words,…

Computation and Language · Computer Science 2017-11-21 Moontae Lee , David Mimno

Terms are one of the fundamental mathematical concepts in computing. E.g. every expression characterisable by a context free grammar is a term. We developed a thread-safe Term Library. The biggest challenge is to implement hyper-efficient…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-08-15 J. F. Groote , M. Laveaux , P. H. M. van Spaendonck

Lazy search algorithms have been developed to efficiently solve planning problems in domains where the computational effort is dominated by the cost of edge evaluation. The existing algorithms operate by intelligently balancing…

Robotics · Computer Science 2023-01-16 Shohin Mukherjee , Sandip Aine , Maxim Likhachev

This article considers the parallel machine scheduling problem with step-deteriorating jobs and sequence-dependent setup times. The objective is to minimize the total tardiness by determining the allocation and sequence of jobs on identical…

Optimization and Control · Mathematics 2013-09-06 Peng Guo , Wenming Cheng , Yi Wang

We study prioritized planning for Multi-Agent Path Finding (MAPF). Existing prioritized MAPF algorithms depend on rule-of-thumb heuristics and random assignment to determine a fixed total priority ordering of all agents a priori. We instead…

Artificial Intelligence · Computer Science 2018-12-18 Hang Ma , Daniel Harabor , Peter J. Stuckey , Jiaoyang Li , Sven Koenig

Multilevel association rules explore the concept hierarchy at multiple levels which provides more specific information. Apriori algorithm explores the single level association rules. Many implementations are available of Apriori algorithm.…

Databases · Computer Science 2013-09-11 Arpna Shrivastava , R. C. Jain

Query processing in search engines can be optimized for use for all queries. For this, system component parameters such as the weighting function or the automatic query expansion model can be optimized or learned from past queries. However,…

Information Retrieval · Computer Science 2023-02-23 Josiane Mothe , Md Zia Ullah

We explore the use of the Cell Broadband Engine (Cell/BE for short) for combinatorial optimization applications: we present a parallel version of a constraint-based local search algorithm that has been implemented on a multiprocessor…

Artificial Intelligence · Computer Science 2009-10-08 Salvator Abreu , Daniel Diaz , Philippe Codognet

The task of hyper-parameter optimization (HPO) is burdened with heavy computational costs due to the intractability of optimizing both a model's weights and its hyper-parameters simultaneously. In this work, we introduce a new class of HPO…

Machine Learning · Computer Science 2021-12-14 Mathieu Tuli , Mahdi S. Hosseini , Konstantinos N. Plataniotis

The performance of a constraint model can often be improved by converting a subproblem into a single table constraint (referred to as tabulation). Finding subproblems to tabulate is traditionally a manual and time-intensive process, even…

The multiple-try Metropolis (MTM) algorithm is an extension of the Metropolis-Hastings (MH) algorithm by selecting the proposed state among multiple trials according to some weight function. Although MTM has gained great popularity owing to…

Methodology · Statistics 2022-10-17 Hyunwoong Chang , Changwoo J. Lee , Zhao Tang Luo , Huiyan Sang , Quan Zhou

Executing quantum circuits on currently available quantum computers requires compiling them to a representation that conforms to all restrictions imposed by the targeted architecture. Due to the limited connectivity of the devices' physical…

Quantum Physics · Physics 2023-01-11 Lukas Burgholzer , Sarah Schneider , Robert Wille