A data driven hybrid heuristic for the dial-a-ride problem with time windows

Slim Belhaiza

doi:10.1109/SSCI.2017.8285366

A data driven hybrid heuristic for the dial-a-ride problem with time windows

Slim Belhaiza^*

^*Corresponding author for this work

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

8 Scopus citations

Abstract

The Dial-A-Ride Problem (DARP) consists of designing pick-up and delivery vehicle routing schedules for a set of customers. Commonly, it arises in door-to-door transportation for impaired or elderly people. The main objective is to accommodate as many users as possible with a minimum operation cost. It adds realistic precedence and transit time constraints on the pairing of vehicles and customers. This paper proposes a hybrid evolutionary heuristic for the dial-a-ride problem with time windows (DARPTW). It combines evolutionary crossover operators with a hybridized VNS algorithm. Data extracted from routes with DARP infeasibilities are used to guide customized local search operators. Using route duration minimization as its main objective, the competitiveness of the proposed heuristic is tested on benchmark instances.

Original language	English
Title of host publication	2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-8
Number of pages	8
ISBN (Electronic)	9781538627259
DOIs	https://doi.org/10.1109/SSCI.2017.8285366
State	Published - 1 Jul 2017

Publication series

Name	2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings
Volume	2018-January

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

Dial-A-Ride Problem
Evolutionary heuristic
Tabu Search
Time Windows
Variable Neighborhood Search

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Control and Optimization

Access to Document

10.1109/SSCI.2017.8285366

Cite this

Belhaiza, S. (2017). A data driven hybrid heuristic for the dial-a-ride problem with time windows. In 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings (pp. 1-8). (2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSCI.2017.8285366

@inproceedings{3ac9be86a29c432d961d0a3012d2f416,

title = "A data driven hybrid heuristic for the dial-a-ride problem with time windows",

abstract = "The Dial-A-Ride Problem (DARP) consists of designing pick-up and delivery vehicle routing schedules for a set of customers. Commonly, it arises in door-to-door transportation for impaired or elderly people. The main objective is to accommodate as many users as possible with a minimum operation cost. It adds realistic precedence and transit time constraints on the pairing of vehicles and customers. This paper proposes a hybrid evolutionary heuristic for the dial-a-ride problem with time windows (DARPTW). It combines evolutionary crossover operators with a hybridized VNS algorithm. Data extracted from routes with DARP infeasibilities are used to guide customized local search operators. Using route duration minimization as its main objective, the competitiveness of the proposed heuristic is tested on benchmark instances.",

keywords = "Dial-A-Ride Problem, Evolutionary heuristic, Tabu Search, Time Windows, Variable Neighborhood Search",

author = "Slim Belhaiza",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.",

year = "2017",

month = jul,

day = "1",

doi = "10.1109/SSCI.2017.8285366",

language = "English",

series = "2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1--8",

booktitle = "2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings",

address = "United States",

}

Belhaiza, S 2017, A data driven hybrid heuristic for the dial-a-ride problem with time windows. in 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings. 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-8. https://doi.org/10.1109/SSCI.2017.8285366

A data driven hybrid heuristic for the dial-a-ride problem with time windows. / Belhaiza, Slim.
2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-8 (2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings; Vol. 2018-January).

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

TY - GEN

T1 - A data driven hybrid heuristic for the dial-a-ride problem with time windows

AU - Belhaiza, Slim

PY - 2017/7/1

Y1 - 2017/7/1

N2 - The Dial-A-Ride Problem (DARP) consists of designing pick-up and delivery vehicle routing schedules for a set of customers. Commonly, it arises in door-to-door transportation for impaired or elderly people. The main objective is to accommodate as many users as possible with a minimum operation cost. It adds realistic precedence and transit time constraints on the pairing of vehicles and customers. This paper proposes a hybrid evolutionary heuristic for the dial-a-ride problem with time windows (DARPTW). It combines evolutionary crossover operators with a hybridized VNS algorithm. Data extracted from routes with DARP infeasibilities are used to guide customized local search operators. Using route duration minimization as its main objective, the competitiveness of the proposed heuristic is tested on benchmark instances.

AB - The Dial-A-Ride Problem (DARP) consists of designing pick-up and delivery vehicle routing schedules for a set of customers. Commonly, it arises in door-to-door transportation for impaired or elderly people. The main objective is to accommodate as many users as possible with a minimum operation cost. It adds realistic precedence and transit time constraints on the pairing of vehicles and customers. This paper proposes a hybrid evolutionary heuristic for the dial-a-ride problem with time windows (DARPTW). It combines evolutionary crossover operators with a hybridized VNS algorithm. Data extracted from routes with DARP infeasibilities are used to guide customized local search operators. Using route duration minimization as its main objective, the competitiveness of the proposed heuristic is tested on benchmark instances.

KW - Dial-A-Ride Problem

KW - Evolutionary heuristic

KW - Tabu Search

KW - Time Windows

KW - Variable Neighborhood Search

UR - https://www.scopus.com/pages/publications/85046091180

U2 - 10.1109/SSCI.2017.8285366

DO - 10.1109/SSCI.2017.8285366

M3 - Conference contribution

AN - SCOPUS:85046091180

T3 - 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings

SP - 1

EP - 8

BT - 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

A data driven hybrid heuristic for the dial-a-ride problem with time windows

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this