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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Main Author: Rocchi, Elena <1986>
Other Authors: Maniezzo, Vittorio
Format: Doctoral Thesis
Language:en
Published: Alma Mater Studiorum - Università di Bologna 2016
Subjects:
Online Access:http://amsdottorato.unibo.it/7301/
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spelling 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
collection NDLTD
language en
format Doctoral Thesis
sources NDLTD
topic INF/01 Informatica
spellingShingle 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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