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  • Search: subject:"Population-based methods"
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Subject
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Evolutionary algorithm 2 Evolutionärer Algorithmus 2 Mathematical programming 2 Mathematische Optimierung 2 Population-based methods 2 Theorie 2 Theory 2 Algorithm 1 Algorithmus 1 Atomic clusters 1 Basin Hopping 1 Bilevel optimization 1 Disk and sphere packing 1 Diversification 1 Error bound 1 Evolutionary Algorithms 1 Global Optimization 1 Global optimization 1 Heuristics 1 Heuristik 1 Iterative heuristics 1 Memetic algorithms 1 Neighborhood structures 1 Optimistic bilevel problem 1 Perturbation method 1 Pessimistic bilevel problem 1 Population based methods 1
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CC license 1 Free 1 Undetermined 1
Type of publication
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Article 3
Type of publication (narrower categories)
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Article in journal 2 Aufsatz in Zeitschrift 2
Language
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English 2 Undetermined 1
Author
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Locatelli, Marco 2 Schoen, Fabio 2 Antoniou, Margarita 1 Maischberger, Mirko 1 Papa, Gregor 1 Sinha, Ankur 1
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Computers & operations research : and their applications to problems of world concern ; an international journal 1 European Journal of Operational Research 1 Operations research perspectives 1
Source
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ECONIS (ZBW) 2 RePEc 1
Showing 1 - 3 of 3
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δ-perturbation of bilevel optimization problems : an error bound analysis
Antoniou, Margarita; Sinha, Ankur; Papa, Gregor - In: Operations research perspectives 13 (2024), pp. 1-19
In this paper, we analyze a perturbed formulation of bilevel optimization problems, which we refer to as δ-perturbed formulation. The δ-perturbed formulation allows to handle the lower level optimization problem efficiently when there are multiple lower level optimal solutions. By using an...
Persistent link: https://www.econbiz.de/10015372639
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Differential evolution methods based on local searches
Locatelli, Marco; Maischberger, Mirko; Schoen, Fabio - In: Computers & operations research : and their … 43 (2014), pp. 169-180
Persistent link: https://www.econbiz.de/10010241967
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Local search based heuristics for global optimization: Atomic clusters and beyond
Locatelli, Marco; Schoen, Fabio - In: European Journal of Operational Research 222 (2012) 1, pp. 1-9
Finding good solutions to large scale, hard, global optimization problems, is a demanding task with many relevant applications. It is well known that, in order to tackle a difficult problem, an algorithm has to incorporate all of the available information on the problem domain. However, as we...
Persistent link: https://www.econbiz.de/10011052707
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