Katalog : Details

Ulrich Vogel

A flexible metaheuristic framework for solving rich vehicle routing problems

ISBN:

978-3-8440-0674-2

Reihe:

Wirtschaftsinformatik und Operations Research
Herausgeber: Prof. Dr. Ulrich Derigs
Köln

Band:

Schlagwörter:

rich vehicle routing problems; software framework; metaheuristics

Publikationsart:

Dissertation

Sprache:

Englisch

Seiten:

206 Seiten

Abbildungen:

34 Abbildungen

Gewicht:

305 g

Format:

21 x 14,8 cm

Bindung:

Paperback

Preis:

49,80 € / 99,60 SFr

Erscheinungsdatum:

Januar 2012

Kaufen:

Download:

Verfügbare Online-Dokumente zu diesem Titel:

Sie benötigen den Adobe Reader, um diese Dateien ansehen zu können. Hier erhalten Sie eine kleine Hilfe und Informationen, zum Download der PDF-Dateien.

Bitte beachten Sie, dass die Online-Dokumente nicht ausdruckbar und nicht editierbar sind.
Bitte beachten Sie auch weitere Informationen unter: Hilfe und Informationen.


	Dokument		Abstract / Kurzzusammenfassung
	Dateiart		PDF
	Kosten		frei
	Aktion		Anzeigen der Datei - 106 kB (108436 Byte)
	Aktion		Download der Datei - 106 kB (108436 Byte)


	Dokument		Gesamtdokument
	Dateiart		PDF
	Kosten		37,35 EUR
	Aktion		Zahlungspflichtig kaufen und anzeigen der Datei - 2,2 MB (2257632 Byte)
	Aktion		Zahlungspflichtig kaufen und download der Datei - 2,2 MB (2257632 Byte)


	Dokument		Inhaltsverzeichnis
	Dateiart		PDF
	Kosten		frei
	Aktion		Anzeigen der Datei - 136 kB (139272 Byte)
	Aktion		Download der Datei - 136 kB (139272 Byte)

Benutzereinstellungen für registrierte Online-Kunden

Sie können hier Ihre Adressdaten ändern sowie bereits georderte Dokumente erneut aufrufen.

Benutzer:	Nicht angemeldet
Aktionen:	Anmelden/Registrieren Passwort vergessen?

Weiterempfehlung:

Sie möchten diesen Titel weiterempfehlen?

Rezensionsexemplar

Hier können Sie ein Rezensionsexemplar bestellen.

Verlinken

Sie möchten diese Seite verlinken? Hier klicken.

Zusammenfassung

Route planning is one of the most studied research topics in the operations research area. While the standard vehicle routing problem (VRP) is the classical problem formulation, additional requirements arising from practical scenarios such as time windows or vehicle compartments are covered in a wide range of so-called rich VRPs. Many solution algorithms for various VRP variants have been developed over time as well, especially within the class of so-called metaheuristics. In practice, routing software must be tailored to the business rules and planning problems of a specific company to provide valuable decision support. This also concerns the embedded solution methods of such decision support systems. Yet, publications dealing with flexibility and customization of VRP heuristics are rare. To fill this gap this thesis describes the design of a flexible framework to facilitate and accelerate the development of custom metaheuristics for the solution of a broad range of rich VRPs. The first part of the thesis provides background information to the reader on the field of vehicle routing problems and on metaheuristic solution methods - the most common and widely-used solution methods to solve VRPs. Specifically, emphasis is put on methods based on local search (for intensification of the search) and large neighborhood search (for diversification of the search), which are combined to hybrid methods and which are the foundation of the proposed framework.
Then, the main part elaborates on the concepts and the design of the metaheuristic VRP framework. The framework fulfills requirements of flexibility, simplicity, accuracy, and speed, enforcing the structuring and standardization of the development process and enabling the reuse of code. Essentially, it provides a library of well-known and accepted heuristics for the standard VRP together with a set of mechanisms to adapt these heuristics to specific VRPs. Heuristics and adaptation mechanisms such as templates for user-definable checking functions are explained on a pseudocode level first, and the most relevant classes of a reference implementation using the Microsoft .NET framework are presented afterwards. Finally, the third part of the thesis demonstrates the use of the framework for developing problem-specific solution methods by exemplifying specific customizations for five rich VRPs with diverse characteristics, namely the VRP with time windows, the VRP with compartments, the split delivery VRP, the periodic VRP, and the truck and trailer routing problem. These adaptations refer to data structures and neighborhood search methods and can serve as a source of inspiration to the reader when designing algorithms for new, so far unstudied VRPs. Computational results are presented to show the effectiveness and efficiency of the proposed framework and methods, which are competitive with current state-of-the-art solvers of the literature. Special attention is given to the overall robustness of heuristics, which is an important aspect for practical application.