Model-Based Heuristics for Combinatorial Optimization
Many problems arising in several and different areas of human knowledge share the characteristic of being intractable in real cases. The relevance of the solution of these problems, linked to their domain of action, has given birth to many frameworks of algorithms for solving them. Traditional solut...
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ndltd-unibo.it-oai-amsdottorato.cib.unibo.it-73012016-08-06T06:02:38Z Model-Based Heuristics for Combinatorial Optimization Rocchi, Elena <1986> INF/01 Informatica Many problems arising in several and different areas of human knowledge share the characteristic of being intractable in real cases. The relevance of the solution of these problems, linked to their domain of action, has given birth to many frameworks of algorithms for solving them. Traditional solution paradigms are represented by exact and heuristic algorithms. In order to overcome limitations of both approaches and obtain better performances, tailored combinations of exact and heuristic methods have been studied, giving birth to a new paradigm for solving hard combinatorial optimization problems, constituted by model-based metaheuristics. In the present thesis, we deepen the issue of model-based metaheuristics, and present some methods, belonging to this class, applied to the solution of combinatorial optimization problems. Alma Mater Studiorum - Università di Bologna Maniezzo, Vittorio 2016-05-13 Doctoral Thesis PeerReviewed application/pdf en http://amsdottorato.unibo.it/7301/ info:eu-repo/semantics/openAccess |
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en |
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Doctoral Thesis |
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INF/01 Informatica |
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INF/01 Informatica Rocchi, Elena <1986> Model-Based Heuristics for Combinatorial Optimization |
description |
Many problems arising in several and different areas of human knowledge share the characteristic of being intractable in real cases. The relevance of the solution of these problems, linked to their domain of action, has given birth to many frameworks of algorithms for solving them. Traditional solution paradigms are represented by exact and heuristic algorithms. In order to overcome limitations of both approaches and obtain better performances, tailored combinations of exact and heuristic methods have been studied, giving birth to a new paradigm for solving hard combinatorial optimization
problems, constituted by model-based metaheuristics. In the present thesis, we deepen the issue of model-based metaheuristics, and present some methods, belonging to this class, applied to the solution of combinatorial
optimization problems. |
author2 |
Maniezzo, Vittorio |
author_facet |
Maniezzo, Vittorio Rocchi, Elena <1986> |
author |
Rocchi, Elena <1986> |
author_sort |
Rocchi, Elena <1986> |
title |
Model-Based Heuristics for Combinatorial Optimization |
title_short |
Model-Based Heuristics for Combinatorial Optimization |
title_full |
Model-Based Heuristics for Combinatorial Optimization |
title_fullStr |
Model-Based Heuristics for Combinatorial Optimization |
title_full_unstemmed |
Model-Based Heuristics for Combinatorial Optimization |
title_sort |
model-based heuristics for combinatorial optimization |
publisher |
Alma Mater Studiorum - Università di Bologna |
publishDate |
2016 |
url |
http://amsdottorato.unibo.it/7301/ |
work_keys_str_mv |
AT rocchielena1986 modelbasedheuristicsforcombinatorialoptimization |
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