Search Results - Per-Instance Algorithm Configuration

Per-Instance Algorithm Configuration in Homogeneous Instance Spaces: A Use Case in Reconfigurable Assembly Systems by Guzman Vargas, Daniel, Gautama, Sidharta, Uzunosmanoglu, Mehmet, Raa, Birger, Limère, Veronique

“…-all” approach, recent studies have shown the potential of per-instance algorithm configuration (PIAC…”
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Per-instance algorithm configuration for production planning in a reconfigurable assembly system by Vargas, Daniel Guzman, Gautama, Sidharta, Uzunosmanoglu, Mehmet, Raa, Birger, Limere, Veronique

“… solution of these problems. In this work, we investigate the use of Per-instance algorithm configuration (PIAC…”
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Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP by Vinzent Seiler, Moritz, Rook, Jeroen, Heins, Jonathan, Ludger Preub, Oliver, Bossek, Jakob, Trautmann, Heike

“… We explore the potential of Per-Instance Algorithm Configuration (PIAC) by using Reinforcement Learning (RL…”
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Stochastic local search and parameters recommendation: a case study on flowshop problems by Pavelski, Lucas M., Delgado, Myriam, Kessaci, Marie‐Éléonore, Freitas, Alex A.

“…‐instance Algorithm Configuration Problem, is still considered a challenging task. This paper investigates the use of meta…”
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Beyond Landscape Analysis: DynamoRep Features For Capturing Algorithm-Problem Interaction In Single-Objective Continuous Optimization by Cenikj, Gjorgjina, Petelin, Gašper, Doerr, Carola, Korošec, Peter, Eftimov, Tome

“… of optimization algorithms, and the quality of existing problem benchmarks, as well as for automated per-instance algorithm selection and configuration approaches…”
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Automated Algorithm Selection: Survey and Perspectives by Kerschke, Pascal, Hoos, Holger H, Neumann, Frank, Trautmann, Heike

“…It has long been observed that for practically any computational problem that has been intensely studied, different instances are best solved using different algorithms…”
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Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes by Eftimov, Tome, Popovski, Gorjan, Renau, Quentin, Korosec, Peter, Doerr, Carola

“…Automated per-instance algorithm selection and configuration have shown promising performances for a number of classic optimization problems, including satisfiability, AI planning, and TSP…”
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Elastic Task Offloading and Resource Allocation Over Hybrid Cloud: A Reinforcement Learning Approach by Zhang, Jiayin, Yu, Huiqun, Fan, Guisheng, Li, Zengpeng

“…Hybrid cloud is an emerging computing cloud solution that leverages the power of the public cloud, without abandoning the computation resources of existing…”
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Characterising fitness landscapes with fitness-probability cloud and its applications to algorithm configuration by Lu, Guanzhou

“… instances, even to dynamically determine the best algorithm configuration during different stages of a search algorithm…”
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Generating Instances with Performance Differences for More Than Just Two Algorithms by Bossek, Jakob, Wagner, Markus

“… Repeating this process is useful to gain insights into strengths/weaknesses of certain algorithms or to build a set of instances with strong performance differences as a foundation for automatic per…”
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Per-Instance Configuration of the Modularized CMA-ES by Means of Classifier Chains and Exploratory Landscape Analysis by Prager, Raphael Patrick, Trautmann, Heike, Wang, Hao, Back, Thomas H. W., Kerschke, Pascal

“… is not. We propose a well-performing instance-specific algorithm configuration model which selects…”
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An Analysis of Effective Per-instance Tailored GAs for the Permutation Flowshop Scheduling Problem by Bacha, Sarra Zohra Ahmed, Tayeb, Fatima Benbouzid-Si, Benatchba, Karima

“…In this paper, we analyze the results of two hyper-heuristics HHGA and HHabs that generate per-instances genetic algorithms for the permutation flow shop problem…”
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Selection-based Per-Instance Heuristic Generation for Protein Structure Prediction of 2D HP Model by Misir, Mustafa

“… The resulting structure directly relates to the functionalities of the protein. There are a wide range of algorithms to address Protein Structure Prediction as an optimization problem…”
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Performance prediction using support vector machine for the configuration of optimization algorithms by Afia, Abdellatif El, Sarhani, Malek

“… Our approach consists of advocating making the decision of finding the most suitable configuration on a per-instance analysis based on a supervised machine learning model…”
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Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes by Tome Eftimov, Popovski, Gorjan, Renau, Quentin, Korosec, Peter, Doerr, Carola

“…Automated per-instance algorithm selection and configuration have shown promising performances for a number of classic optimization problems, including satisfiability, AI planning, and TSP…”
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The Algorithm Configuration Problem by Iommazzo, Gabriele, D'Ambrosio, Claudia, Frangioni, Antonio, Liberti, Leo

“… This article delves into the Algorithm Configuration Problem, focused on optimizing parametrized algorithms for solving specific instances of decision/optimization problems…”
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RF+clust for Leave-One-Problem-Out Performance Prediction by Nikolikj, Ana, Doerr, Carola, Tome Eftimov

“…Per-instance automated algorithm configuration and selection are gaining significant moments in evolutionary computation in recent years…”
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Distance approximation to support customer selection in vehicle routing problems by Akkerman, Fabian, Mes, Martijn

“… The model is validated on a fictional case with different spatial instances considering both a backordering and lost sales configuration, and on a…”
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ASlib: A benchmark library for algorithm selection by Bischl, Bernd, Kerschke, Pascal, Kotthoff, Lars, Lindauer, Marius, Malitsky, Yuri, Fréchette, Alexandre, Hoos, Holger, Hutter, Frank, Leyton-Brown, Kevin, Tierney, Kevin, Vanschoren, Joaquin

“…The task of algorithm selection involves choosing an algorithm from a set of algorithms on a per-instance basis in order to exploit the varying performance of algorithms over a set of instances…”
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Automated Algorithm Selection: Survey and Perspectives by Kerschke, Pascal, Hoos, Holger H, Neumann, Frank, Trautmann, Heike

“…It has long been observed that for practically any computational problem that has been intensely studied, different instances are best solved using different algorithms…”
Get full text