A new fast large neighbourhood search for service network design with asset balance constraints

Ruibin Bai; John R. Woodward; Nachiappan Subramanian

doi:10.1109/SSCI.2016.7850084

A new fast large neighbourhood search for service network design with asset balance constraints

Ruibin Bai
, John R. Woodward
, Nachiappan Subramanian

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

The service network design problem (SNDP) is a fundamental problem in consolidated freight transportation. It involves the determination of an efficient transportation network and the scheduling details of the corresponding services. Compared to vehicle routing problems, SNDP can model transfers and consolidations on a multi-modal freight network. The problem is often formulated as a mixed integer programming problem and is NP-Hard. In this research, we propose a new efficient large neighbourhood search function that can handle the constraints more efficiently. The effectiveness of this new neighbourhood is evaluated in a tabu search metaheuristic (TS) and a GLS guided local search (GLS) method. Experimental results based on a set of well-known benchmark instances show that the new neighbourhood performs significantly better than the previous arc-flipping neighbourhood. The neighbourhood function is also applicable in other optimisation problems with similar discrete constraints.

Original language	English
Title of host publication	2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509042401
DOIs	https://doi.org/10.1109/SSCI.2016.7850084
Publication status	Published - 9 Feb 2017
Event	2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016 - Athens, Greece Duration: 6 Dec 2016 → 9 Dec 2016

Publication series

Name	2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016

Conference

Conference	2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016
Country/Territory	Greece
City	Athens
Period	6/12/16 → 9/12/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Information Systems and Management
Control and Optimization

Access to Document

10.1109/SSCI.2016.7850084

Cite this

Bai, R., Woodward, J. R., & Subramanian, N. (2017). A new fast large neighbourhood search for service network design with asset balance constraints. In 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016 Article 7850084 (2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSCI.2016.7850084

@inproceedings{2ade69d653f14057aae606fe80343b91,

title = "A new fast large neighbourhood search for service network design with asset balance constraints",

abstract = "The service network design problem (SNDP) is a fundamental problem in consolidated freight transportation. It involves the determination of an efficient transportation network and the scheduling details of the corresponding services. Compared to vehicle routing problems, SNDP can model transfers and consolidations on a multi-modal freight network. The problem is often formulated as a mixed integer programming problem and is NP-Hard. In this research, we propose a new efficient large neighbourhood search function that can handle the constraints more efficiently. The effectiveness of this new neighbourhood is evaluated in a tabu search metaheuristic (TS) and a GLS guided local search (GLS) method. Experimental results based on a set of well-known benchmark instances show that the new neighbourhood performs significantly better than the previous arc-flipping neighbourhood. The neighbourhood function is also applicable in other optimisation problems with similar discrete constraints.",

author = "Ruibin Bai and Woodward, \{John R.\} and Nachiappan Subramanian",

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year = "2017",

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doi = "10.1109/SSCI.2016.7850084",

language = "English",

series = "2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016",

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Bai, R, Woodward, JR & Subramanian, N 2017, A new fast large neighbourhood search for service network design with asset balance constraints. in 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016., 7850084, 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016, Athens, Greece, 6/12/16. https://doi.org/10.1109/SSCI.2016.7850084

A new fast large neighbourhood search for service network design with asset balance constraints. / Bai, Ruibin; Woodward, John R.; Subramanian, Nachiappan.
2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016. Institute of Electrical and Electronics Engineers Inc., 2017. 7850084 (2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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N2 - The service network design problem (SNDP) is a fundamental problem in consolidated freight transportation. It involves the determination of an efficient transportation network and the scheduling details of the corresponding services. Compared to vehicle routing problems, SNDP can model transfers and consolidations on a multi-modal freight network. The problem is often formulated as a mixed integer programming problem and is NP-Hard. In this research, we propose a new efficient large neighbourhood search function that can handle the constraints more efficiently. The effectiveness of this new neighbourhood is evaluated in a tabu search metaheuristic (TS) and a GLS guided local search (GLS) method. Experimental results based on a set of well-known benchmark instances show that the new neighbourhood performs significantly better than the previous arc-flipping neighbourhood. The neighbourhood function is also applicable in other optimisation problems with similar discrete constraints.

AB - The service network design problem (SNDP) is a fundamental problem in consolidated freight transportation. It involves the determination of an efficient transportation network and the scheduling details of the corresponding services. Compared to vehicle routing problems, SNDP can model transfers and consolidations on a multi-modal freight network. The problem is often formulated as a mixed integer programming problem and is NP-Hard. In this research, we propose a new efficient large neighbourhood search function that can handle the constraints more efficiently. The effectiveness of this new neighbourhood is evaluated in a tabu search metaheuristic (TS) and a GLS guided local search (GLS) method. Experimental results based on a set of well-known benchmark instances show that the new neighbourhood performs significantly better than the previous arc-flipping neighbourhood. The neighbourhood function is also applicable in other optimisation problems with similar discrete constraints.

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M3 - Conference contribution

AN - SCOPUS:85016002835

T3 - 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016

BT - 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016

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Bai R, Woodward JR, Subramanian N. A new fast large neighbourhood search for service network design with asset balance constraints. In 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016. Institute of Electrical and Electronics Engineers Inc. 2017. 7850084. (2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016). doi: 10.1109/SSCI.2016.7850084

A new fast large neighbourhood search for service network design with asset balance constraints

Abstract

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UN SDGs

ASJC Scopus subject areas

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