A heuristic algorithm for the earliest arrival flow with multiple sources

Hong Zheng, Yi-Chang Chiu, Pitu B. Mirchandani

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

This paper presents a heuristic algorithm for the earliest arrival flow problem. Existing exact algorithms, even polynomial in the output size, contain submodular function optimization as a frequently called subroutine, and thus are not practical in real-life applications. In this paper we propose an algorithm that does not involve the submodular function optimization. Although solving an EAF nearoptimal, the algorithm is remarkably simple and efficient as it only involves shortest path computations on a static network. A numerical example illustrates how the algorithm works. As an application, we demonstrate the algorithm’s solution quality and computational performance by solving a real-size network.

Original languageEnglish (US)
Article numberA004
Pages (from-to)169-189
Number of pages21
JournalJournal of Mathematical Modelling and Algorithms
Volume13
Issue number2
DOIs
StatePublished - 2014

Fingerprint

Heuristic algorithms
Heuristic algorithm
Submodular Function
Function Optimization
Exact Algorithms
Shortest path
Subroutines
Numerical Examples
Polynomial
Polynomials
Output
Demonstrate

Keywords

  • Dynamic flows
  • Earliest arrival flows
  • Flows over time
  • Heuristics
  • Network flows

ASJC Scopus subject areas

  • Applied Mathematics
  • Modeling and Simulation

Cite this

A heuristic algorithm for the earliest arrival flow with multiple sources. / Zheng, Hong; Chiu, Yi-Chang; Mirchandani, Pitu B.

In: Journal of Mathematical Modelling and Algorithms, Vol. 13, No. 2, A004, 2014, p. 169-189.

Research output: Contribution to journalArticle

@article{eeb1f3a4224549b99693b480ef3dbc10,
title = "A heuristic algorithm for the earliest arrival flow with multiple sources",
abstract = "This paper presents a heuristic algorithm for the earliest arrival flow problem. Existing exact algorithms, even polynomial in the output size, contain submodular function optimization as a frequently called subroutine, and thus are not practical in real-life applications. In this paper we propose an algorithm that does not involve the submodular function optimization. Although solving an EAF nearoptimal, the algorithm is remarkably simple and efficient as it only involves shortest path computations on a static network. A numerical example illustrates how the algorithm works. As an application, we demonstrate the algorithm’s solution quality and computational performance by solving a real-size network.",
keywords = "Dynamic flows, Earliest arrival flows, Flows over time, Heuristics, Network flows",
author = "Hong Zheng and Yi-Chang Chiu and Mirchandani, {Pitu B.}",
year = "2014",
doi = "10.1007/s10852-013-9226-8",
language = "English (US)",
volume = "13",
pages = "169--189",
journal = "Journal of Mathematical Modelling and Algorithms",
issn = "1570-1166",
publisher = "Springer Netherlands",
number = "2",

}

TY - JOUR

T1 - A heuristic algorithm for the earliest arrival flow with multiple sources

AU - Zheng, Hong

AU - Chiu, Yi-Chang

AU - Mirchandani, Pitu B.

PY - 2014

Y1 - 2014

N2 - This paper presents a heuristic algorithm for the earliest arrival flow problem. Existing exact algorithms, even polynomial in the output size, contain submodular function optimization as a frequently called subroutine, and thus are not practical in real-life applications. In this paper we propose an algorithm that does not involve the submodular function optimization. Although solving an EAF nearoptimal, the algorithm is remarkably simple and efficient as it only involves shortest path computations on a static network. A numerical example illustrates how the algorithm works. As an application, we demonstrate the algorithm’s solution quality and computational performance by solving a real-size network.

AB - This paper presents a heuristic algorithm for the earliest arrival flow problem. Existing exact algorithms, even polynomial in the output size, contain submodular function optimization as a frequently called subroutine, and thus are not practical in real-life applications. In this paper we propose an algorithm that does not involve the submodular function optimization. Although solving an EAF nearoptimal, the algorithm is remarkably simple and efficient as it only involves shortest path computations on a static network. A numerical example illustrates how the algorithm works. As an application, we demonstrate the algorithm’s solution quality and computational performance by solving a real-size network.

KW - Dynamic flows

KW - Earliest arrival flows

KW - Flows over time

KW - Heuristics

KW - Network flows

UR - http://www.scopus.com/inward/record.url?scp=84922530787&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84922530787&partnerID=8YFLogxK

U2 - 10.1007/s10852-013-9226-8

DO - 10.1007/s10852-013-9226-8

M3 - Article

AN - SCOPUS:84922530787

VL - 13

SP - 169

EP - 189

JO - Journal of Mathematical Modelling and Algorithms

JF - Journal of Mathematical Modelling and Algorithms

SN - 1570-1166

IS - 2

M1 - A004

ER -