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ORCID9th LION 2015: Lille, France
- Clarisse Dhaenens
, Laetitia Jourdan, Marie-Eléonore Marmion:
Learning and Intelligent Optimization - 9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers. Lecture Notes in Computer Science 8994, Springer 2015, ISBN 978-3-319-19083-9 - Marius Lindauer, Holger H. Hoos, Frank Hutter:
From Sequential Algorithm Selection to Parallel Portfolio Selection. 1-16 - Kevin Tierney, Yuri Malitsky:
An Algorithm Selection Benchmark of the Container Pre-marshalling Problem. 17-22 - Mustafa Misir, Stephanus Daniel Handoko, Hoong Chuin Lau:
ADVISER: A Web-Based Algorithm Portfolio Deviser. 23-28 - Zhen-Zhen Li, Zhuo-Yao Zhong, Lian-Wen Jin:
Identifying Best Hyperparameters for Deep Architectures Using Random Forests. 29-42 - Sepp Hartung, Holger H. Hoos:
Programming by Optimisation Meets Parameterised Algorithmics: A Case Study for Cluster Editing. 43-58 - Mustafa Misir, Stephanus Daniel Handoko, Hoong Chuin Lau:
OSCAR: Online Selection of Algorithm Portfolios with Case Study on Memetic Algorithms. 59-73 - Willem Van Onsem, Bart Demoen, Patrick De Causmaecker:
Learning a Hidden Markov Model-Based Hyper-heuristic. 74-88 - Martin Drozdik, Hernán E. Aguirre, Youhei Akimoto, Kiyoshi Tanaka:
Comparison of Parameter Control Mechanisms in Multi-objective Differential Evolution. 89-103 - Andy J. Keane:
Genetic Programming, Logic Design and Case-Based Reasoning for Obstacle Avoidance. 104-118 - Eduardo Lalla-Ruiz, Stefan Voß:
Minimizing Total Tardiness on Identical Parallel Machines Using VNS with Learning Memory. 119-124 - Oliver Skroch:
Dynamic Service Selection with Optimal Stopping and 'Trivial Choice'. 125-130 - Shota Eguchi, Yuki Matsugano, Hirokazu Sakaguchi, Satoshi Ono, Hisato Fukuda, Ryo Furukawa, Hiroshi Kawasaki:
A Comparative Study on Self-Adaptive Differential Evolution Algorithms for Test Functions and a Real-World Problem. 131-136 - Pierre Desport, Matthieu Basseur, Adrien Goëffon, Frédéric Lardeux, Frédéric Saubion:
Empirical Analysis of Operators for Permutation Based Problems. 137-150 - Marie-Eléonore Marmion, Olivier Regnier-Coudert:
Fitness Landscape of the Factoradic Representation on the Permutation Flowshop Scheduling Problem. 151-164 - Matthieu Basseur, Adrien Goëffon, Hugo Traverson:
Exploring Non-neutral Landscapes with Neutrality-Based Local Search. 165-169 - Leticia Vargas, Nicolas Jozefowiez, Sandra Ulrich Ngueveu:
A Selector Operator-Based Adaptive Large Neighborhood Search for the Covering Tour Problem. 170-185 - Alan Tus, Andrea Rendl, Günther R. Raidl:
Metaheuristics for the Two-Dimensional Container Pre-Marshalling Problem. 186-201 - Lars Kotthoff, Pascal Kerschke, Holger H. Hoos, Heike Trautmann:
Improving the State of the Art in Inexact TSP Solving Using Per-Instance Algorithm Selection. 202-217 - Eduardo Lalla-Ruiz, Stefan Voß:
A Biased Random-Key Genetic Algorithm for the Multiple Knapsack Assignment Problem. 218-222 - Sophie Jacquin, Laetitia Jourdan, El-Ghazali Talbi:
DYNAMOP Applied to the Unit Commitment Problem. 223-228 - Madalina M. Drugan:
Scalarized Lower Upper Confidence Bound Algorithm. 229-235 - Helga Ingimundardottir, Thomas Philip Runarsson:
Generating Training Data for Learning Linear Composite Dispatching Rules for Scheduling. 236-248 - Brahim Chabane, Matthieu Basseur, Jin-Kao Hao:
A Practical Case of the Multiobjective Knapsack Problem: Design, Modelling, Tests and Analysis. 249-255 - Paul Feliot, Julien Bect, Emmanuel Vázquez:
A Bayesian Approach to Constrained Multi-objective Optimization. 256-261 - Alexandre Quemy, Marc Schoenauer, Vincent Vidal, Johann Dréo, Pierre Savéant:
Solving Large MultiZenoTravel Benchmarks with Divide-and-Evolve. 262-267 - Chu-Min Li, Hua Jiang, Ruchu Xu:
Incremental MaxSAT Reasoning to Reduce Branches in a Branch-and-Bound Algorithm for MaxClique. 268-274 - Alexey Nikolaev, Mikhail Batsyn, Pablo San Segundo:
Reusing the Same Coloring in the Child Nodes of the Search Tree for the Maximum Clique Problem. 275-280 - Mickaël Binois, David Ginsbourger, Olivier Roustant:
A Warped Kernel Improving Robustness in Bayesian Optimization Via Random Embeddings. 281-286 - Hossein Mohammadi, Rodolphe Le Riche, Eric Touboul:
Making EGO and CMA-ES Complementary for Global Optimization. 287-292 - Benjamin Fisset, Clarisse Dhaenens, Laetitia Jourdan:
MO-Mine_clust: A Framework for Multi-objective Clustering. 293-305 - Andrew J. Parkes, Ender Özcan, Daniel Karapetyan:
A Software Interface for Supporting the Application of Data Science to Optimisation. 306-311
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