DocumentCode
188519
Title
Constraint-Based Local Search for the Distance- and Capacity-Bounded Network Design Problem
Author
Arbelaez, Alejandro ; Mehta, Deepak ; O´Sullivan, Barry ; Quesada, Luis
Author_Institution
Insight Centre for Data Analytics, Univ. Coll. Cork, Cork, Ireland
fYear
2014
fDate
10-12 Nov. 2014
Firstpage
178
Lastpage
185
Abstract
Many network design problems arising in the fields of transportation, distribution and logistics require clients to be connected to facilities through a set of carriers subject to distance and capacity constraints. Here a carrier could be a cable, vehicle, salesman etc. The distance from a facility to client using a carrier could be expressed as signal loss, time spent, path length, etc. The capacity of a carrier could be interpreted as the maximum number of commodities that a carrier can carry, the maximum number of clients or links that a single carrier can visit, etc. The main decisions are to determine the number of carriers, assign clients to carriers, and design a network for each carrier subject to distance, capacity and some side constraints. In this paper, we focus on the Cable Routing Problem (CRP), which is NP-hard. We present a constraint-based local search algorithm and two efficient local move operators. The effectiveness of our approach is demonstrated by experimenting with 300 instances of the CRP taken from real-world passive optical network deployments in Ireland. The results show that our algorithm can scale to very large problem instances and it can compute good quality solutions in a very limited time.
Keywords
computational complexity; logistics; network theory (graphs); transportation; CRP; Ireland; NP-hard problem; cable routing problem; capacity-bounded network design problem; constraint-based local search algorithm; distance-bounded network design problem; logistics; real-world passive optical network deployments; transportation; CSP; Cable Routing Problem; Constraint-based Local Search; Network Design;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference on
Conference_Location
Limassol
ISSN
1082-3409
Type
conf
DOI
10.1109/ICTAI.2014.35
Filename
6984471
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