AGENT-BASED METHODOLOGIES FOR FACILITY LOCATION PROBLEMS

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

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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.

Tipologia di documento:Tesi di dottorato
Parole chiave:Location, Agent-Based models, Simulation, Metaheuristics
Settori scientifico-disciplinari MIUR:Area 01 Scienze matematiche e informatiche > MAT/09 RICERCA OPERATIVA
Coordinatori della Scuola di dottorato:
Coordinatore del Corso di dottoratoe-mail (se nota)
Zollo, Giuseppegiuzollo@unina.it
Tutor della Scuola di dottorato:
Tutor del Corso di dottoratoe-mail (se nota)
Bruno, Giuseppegiubruno@unina.it
Stato del full text:Accessibile
Data:29 Novembre 2009
Numero di pagine:172
Istituzione:Università degli Studi di Napoli "Federico II"
Dipartimento o Struttura:Dipartimento di Ingegneria Economico-Gestionale
Tipo di tesi:Dottorato
Stato dell'Eprint:Inedito
Scuola di dottorato:Ingegneria Industriale
Denominazione del dottorato:Science and Technology Management
Ciclo di dottorato:XXII
Numero di sistema:4257
Depositato il:15 Dicembre 2009 20:48
Ultima modifica:28 Luglio 2010 13:11

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