Genovese, Andrea (2009) AGENT-BASED METHODOLOGIES FOR FACILITY LOCATION PROBLEMS. [Tesi di dottorato] (Inedito)

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Tipologia del documento: Tesi di dottorato
Lingua: English
Titolo: AGENT-BASED METHODOLOGIES FOR FACILITY LOCATION PROBLEMS
Autori:
AutoreEmail
Genovese, Andreaandrea.genovese@unina.it
Data: 29 Novembre 2009
Numero di pagine: 172
Istituzione: Università degli Studi di Napoli Federico II
Dipartimento: Ingegneria economico-gestionale
Scuola di dottorato: Ingegneria industriale
Dottorato: Science and technology management
Ciclo di dottorato: 22
Coordinatore del Corso di dottorato:
nomeemail
Zollo, Giuseppegiuzollo@unina.it
Tutor:
nomeemail
Bruno, Giuseppegiubruno@unina.it
Data: 29 Novembre 2009
Numero di pagine: 172
Parole chiave: Location, Agent-Based models, Simulation, Metaheuristics
Settori scientifico-disciplinari del MIUR: Area 01 - Scienze matematiche e informatiche > MAT/09 - Ricerca operativa
Depositato il: 15 Dic 2009 19:48
Ultima modifica: 30 Apr 2014 19:40
URI: http://www.fedoa.unina.it/id/eprint/4257
DOI: 10.6092/UNINA/FEDOA/4257

Abstract

The high relevance of location problems in the operations research literature arises from their wide spectrum of real applications, including decision optimization in industrial management, logistics, and territorial planning. Most of these optimization problems fall into the class of NP-hard problems, motivating the search for heuristic and approximated algorithms. Currently, a great interest is being devoted to those optimization approaches yielding a concrete integration with spatial analysis instruments (such as Geographical Information Systems) that provide the user with an easy visualization of input data and optimization results. Agent-Based computing was recently proposed as an alternative to mathematical programming in order to solve problems whose domains are concurrently distributed, complex, and heterogeneous, also thanks to the availability of many commercial and open source codes including graphical interfaces for the elements of the problem. In this paper we propose a general Agent-Based framework for modeling various location problems. Together with its description, we present some computational results confirming the suitability and the effectiveness of the proposed approach.

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