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A guided simulated annealing search for solving the pick-up and delivery problem with time windows and capacity constraints

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung

Standard

A guided simulated annealing search for solving the pick-up and delivery problem with time windows and capacity constraints. / Urban, Karsten-Patrick.
in: International Journal of Logistics, Jahrgang 9, Nr. 4, 24.11.2006, S. 369-381.

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung

Harvard

Urban, K-P 2006, 'A guided simulated annealing search for solving the pick-up and delivery problem with time windows and capacity constraints', International Journal of Logistics, Jg. 9, Nr. 4, S. 369-381. https://doi.org/10.1080/13675560600931521

APA

Urban, K.-P. (2006). A guided simulated annealing search for solving the pick-up and delivery problem with time windows and capacity constraints. International Journal of Logistics, 9(4), 369-381. https://doi.org/10.1080/13675560600931521

Vancouver

Urban KP. A guided simulated annealing search for solving the pick-up and delivery problem with time windows and capacity constraints. International Journal of Logistics. 2006 Nov 24;9(4):369-381. doi: 10.1080/13675560600931521

Bibtex

@article{c7f9f05d1e624a83a373a80d727cb3a6,
title = "A guided simulated annealing search for solving the pick-up and delivery problem with time windows and capacity constraints",
abstract = "Routing and scheduling requests with pick-ups and deliveries is still one of the greatest operative challenges in inter-company logistics. Pick-up and delivery activities have to be bundled into efficient routes and their sequence has to be optimised within the routes without violating time and capacity constraints. The objective is to find a schedule of routes with minimal total costs. These costs result from the arising travelling costs, costs due to waiting and service times, and due to dispatching vehicles. This paper presents a guided local search method based on simulated annealing for solving this kind of routing and scheduling problem. Additionally, a new more realistic objective function that covers the total decision-relevant costs is introduced. The computational results show that the algorithm presented clearly outperforms standard implementations of simulated annealing and hill climber search.",
keywords = "Management studies, Applying non-linear cost functions in combinatorial optimisation, Guided neighbourhood search, Metaheuristics, Pick-up and delivery problem, Simulated annealing",
author = "Karsten-Patrick Urban",
note = "Publisher Copyright: {\textcopyright} 2006, Copyright Taylor & Francis Group, LLC.",
year = "2006",
month = nov,
day = "24",
doi = "10.1080/13675560600931521",
language = "English",
volume = "9",
pages = "369--381",
journal = "International Journal of Logistics",
issn = "1367-5567",
publisher = "Taylor & Francis",
number = "4",

}

RIS

TY - JOUR

T1 - A guided simulated annealing search for solving the pick-up and delivery problem with time windows and capacity constraints

AU - Urban, Karsten-Patrick

N1 - Publisher Copyright: © 2006, Copyright Taylor & Francis Group, LLC.

PY - 2006/11/24

Y1 - 2006/11/24

N2 - Routing and scheduling requests with pick-ups and deliveries is still one of the greatest operative challenges in inter-company logistics. Pick-up and delivery activities have to be bundled into efficient routes and their sequence has to be optimised within the routes without violating time and capacity constraints. The objective is to find a schedule of routes with minimal total costs. These costs result from the arising travelling costs, costs due to waiting and service times, and due to dispatching vehicles. This paper presents a guided local search method based on simulated annealing for solving this kind of routing and scheduling problem. Additionally, a new more realistic objective function that covers the total decision-relevant costs is introduced. The computational results show that the algorithm presented clearly outperforms standard implementations of simulated annealing and hill climber search.

AB - Routing and scheduling requests with pick-ups and deliveries is still one of the greatest operative challenges in inter-company logistics. Pick-up and delivery activities have to be bundled into efficient routes and their sequence has to be optimised within the routes without violating time and capacity constraints. The objective is to find a schedule of routes with minimal total costs. These costs result from the arising travelling costs, costs due to waiting and service times, and due to dispatching vehicles. This paper presents a guided local search method based on simulated annealing for solving this kind of routing and scheduling problem. Additionally, a new more realistic objective function that covers the total decision-relevant costs is introduced. The computational results show that the algorithm presented clearly outperforms standard implementations of simulated annealing and hill climber search.

KW - Management studies

KW - Applying non-linear cost functions in combinatorial optimisation

KW - Guided neighbourhood search

KW - Metaheuristics

KW - Pick-up and delivery problem

KW - Simulated annealing

UR - https://www.mendeley.com/catalogue/86bfab48-6499-399b-ac28-0c40a06a0878/

UR - http://www.scopus.com/inward/record.url?scp=84901642165&partnerID=8YFLogxK

U2 - 10.1080/13675560600931521

DO - 10.1080/13675560600931521

M3 - Journal articles

VL - 9

SP - 369

EP - 381

JO - International Journal of Logistics

JF - International Journal of Logistics

SN - 1367-5567

IS - 4

ER -

DOI