An algorithmic framework for the scheduling of construction projects based on ant colony optimization and expert knowledge

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

  • Zhitao Xiong - , University of New South Wales (Autor:in)
  • David Rey - , University of New South Wales (Autor:in)
  • Vinayak V. Dixit - , University of New South Wales (Autor:in)
  • S. Travis Waller - , University of New South Wales (Autor:in)

Abstract

The conduction of construction projects in a road network can result in a reduction of the capacity of the lanes that are under construction or maintenance. In order to mitigate the impact of construction projects, it is critical to find the best schedule in such a way that the effects of road capacity reductions, e.g. traffic delay caused by their presence, is minimized. This article propose a novel formulation for the construction projects scheduling problem using bi-level programming. A solution method is then introduced to solve this challenging scheduling problem with a focus on reducing the number of calculations in the optimization. This is achieved by integrating expert knowledge, which can be used to characterize a good schedule, in the algorithmic framework in charge of determining a near-optimal schedule. Such heuristic information can come from relevant experts or practitioners, or from the literature in this field. A solution algorithm named CoANT based on ant colony optimization is presented and implemented on realistic transportation networks. Our results show that CoANT works fast and is able to provide competitive schedules. As an extensible and modular framework, CoANT can be used by relevant transportation agencies as a decision-aid tool for the coordination of construction projects in road networks.

Details

OriginalspracheEnglisch
Titel2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten2446-2452
Seitenumfang7
ISBN (elektronisch)9781479960781
PublikationsstatusVeröffentlicht - 14 Nov. 2014
Peer-Review-StatusJa
Extern publiziertJa

Publikationsreihe

ReiheInternational Conference on Intelligent Transportation (ITSC)
ISSN2153-0009

Konferenz

Titel2014 17th IEEE International Conference on Intelligent Transportation Systems
KurztitelITSC 2014
Veranstaltungsnummer17
Dauer8 - 11 Oktober 2014
StadtQingdao
LandChina

Externe IDs

ORCID /0000-0002-2939-2090/work/141543821

Schlagworte