Výsledky vyhledávání - "algorithm selection problem"

Meta‐learning how to forecast time series Autor Talagala, Thiyanga S., Hyndman, Rob J., Athanasopoulos, George

“…Features of time series are useful in identifying suitable models for forecasting. We present a general framework, labelled Feature‐based FORecast Model…”
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Applying instance space analysis for metaheuristic selection to the 0–1 multidemand multidimensional knapsack problem Autor Scherer, Matthew E., Hill, Raymond R., Lunday, Brian J., Cox, Bruce A., White, Edward D.

“…The empirical testing of metaheuristic solution methods for optimization applications should consider the effect of the underlying structure of the…”
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Transformer-based placement heuristic for online 2D strip packing problem Autor Kaleta, Mariusz, Kołodziejczyk, Waldemar, Zoltowska, Izabela

“…This paper addresses the online 2D Strip Packing Problem (2D-SPP), where rectangular items must be packed sequentially into a strip of fixed width, with the…”
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Neural-Driven heuristic for strip packing trained with Black-Box optimization Autor Kaleta, Mariusz, Śliwiński, Tomasz

“…We address the well-known NP-hard problem of packing rectangular items into a strip, a problem of significant importance in electronics (e.g., packing…”
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Heuristics for online three-dimensional packing problems and algorithm selection framework for semi-online with full look-ahead Autor Ali, Sara, Ramos, António Galrão, Carravilla, Maria Antónia, Oliveira, José Fernando

“…In online three-dimensional packing problems (3D-PPs), unlike offline problems, items arrive sequentially and require immediate packing decisions without any…”
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A framework to select heuristics for the rectangular two-dimensional strip packing problem Autor Neuenfeldt Júnior, Alvaro, Siluk, Julio, Francescatto, Matheus, Stieler, Gabriel, Disconzi, David

“…•A framework to select improvement heuristics for the rectangular 2D-SPP;•Classification models fitted with supervised machine learning techniques;•15,666…”
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Framework of algorithm portfolios for strip packing problem Autor Piechowiak, Kamil, Drozdowski, Maciej, Sanlaville, Éric

“…In this paper selection of fast algorithm portfolios for 2SP packing problem is considered. The 2SP problem consists in placing rectangles on a strip of the…”
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On normalization and algorithm selection for unsupervised outlier detection Autor Kandanaarachchi, Sevvandi, Muñoz, Mario A., Hyndman, Rob J., Smith-Miles, Kate

“…This paper demonstrates that the performance of various outlier detection methods is sensitive to both the characteristics of the dataset, and the data…”
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Selecting algorithms for large berth allocation problems Autor Wawrzyniak, Jakub, Drozdowski, Maciej, Sanlaville, Éric

“…•Algorithm portfolios solve large berth allocation problems.•Runtime-solution quality trade-off is the core of portfolio construction method.•Algorithm…”
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Improving the state-of-the-art in the Traveling Salesman Problem: An Anytime Automatic Algorithm Selection Autor Huerta, Isaías I., Neira, Daniel A., Ortega, Daniel A., Varas, Vicente, Godoy, Julio, Asín-Achá, Roberto

“…This work presents a new metaheuristic for the euclidean Traveling Salesman Problem (TSP) based on an Anytime Automatic Algorithm Selection model using a…”
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A machine learning approach for predicting the best heuristic for a large scaled Capacitated Lotsizing Problem Autor Kärcher, Jens, Meyr, Herbert

“…For some NP-hard lotsizing problems, many different heuristics exist, but they have different solution qualities and computation times depending on the…”
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Anytime automatic algorithm selection for knapsack Autor Huerta, Isaías I., Neira, Daniel A., Ortega, Daniel A., Varas, Vicente, Godoy, Julio, Asín-Achá, Roberto

“…•New “Anytime” Framework for Automatic Algorithm Selection.•Application of the Anytime Automatic Algorithm Selection Framework to Knapsack.•3 Machine Learning…”
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Meta-learning-Based Model to Select Algorithm for Capacitated Vehicle Routing Problem Autor Sehta, Neha, Thakar, Urjita

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Automated Scheduling Algorithm Selection and Chunk Parameter Calculation in OpenMP Autor Mohammed, Ali, Korndorfer, Jonas H. Muller, Eleliemy, Ahmed, Ciorba, Florina M.

“…Increasing node and cores-per-node counts in supercomputers render scheduling and load balancing critical for exploiting parallelism. OpenMP applications can…”
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An Exploratory Landscape Analysis-Based Benchmark Suite Autor Lang, Ryan Dieter, Engelbrecht, Andries Petrus

“…The choice of which objective functions, or benchmark problems, should be used to test an optimization algorithm is a crucial part of the algorithm selection…”
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SimAS: A simulation‐assisted approach for the scheduling algorithm selection under perturbations Autor Mohammed, Ali, Ciorba, Florina M.

“…Summary Many scientific applications consist of large and computationally intensive loops. Dynamic loop self‐scheduling (DLS) techniques are used to…”
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A Deep Learning-Driven Black-Box Benchmark Generation Method via Exploratory Landscape Analysis Autor Liang, Haoming, Zhao, Fuqing, Xu, Tianpeng, Zhang, Jianlin

“…In the context of algorithm selection, the careful design of benchmark functions and problem instances plays a pivotal role in evaluating the performance of…”
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Constructing a Meta-Learner for Unsupervised Anomaly Detection Autor Gutowska, Malgorzata, Little, Suzanne, Mccarren, Andrew

“…Unsupervised anomaly detection (AD) is critical for a wide range of practical applications, from network security to health and medical tools. Due to the…”
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Optimal decision trees for the algorithm selection problem: integer programming based approaches Autor Vilas Boas, Matheus Guedes, Santos, Haroldo Gambini, Merschmann, Luiz Henrique de Campos, Vanden Berghe, Greet

“…Even though it is well known that for most relevant computational problems, different algorithms may perform better on different classes of problem instances,…”
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Stochastic local search and parameters recommendation: a case study on flowshop problems Autor Pavelski, Lucas M., Delgado, Myriam, Kessaci, Marie‐Éléonore, Freitas, Alex A.

“…The Algorithm Selection Problem (ASP) considers the use of previous knowledge regarding problem features and algorithm performance to recommend the best…”
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