Meta-heuristic approach for high-demand facility locations considering traffic congestion and greenhouse gas emission

Taesung Hwang, Minho Lee, Chungwon Lee, Seungmo Kang

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Large facilities in urban areas, such as storage facilities, distribution centers, schools, department stores, or public service centers, typically generate high volumes of accessing traffic, causing congestion and becoming major sources of greenhouse gas (GHG) emission. In conventional facility-location models, only facility construction costs and fixed transportation costs connecting customers and facilities are included, without consideration of traffic congestion and the subsequent GHG emission costs. This study proposes methods to find high-demand facility locations with incorporation of the traffic congestion and GHG emission costs incurred by both existing roadway traffic and facility users into the total cost. Tabu search and memetic algorithms were developed and tested with a conventional genetic algorithm in a variety of networks to solve the proposed mathematical model. A case study to determine the total number and locations of community service centers under multiple scenarios in Incheon City is then presented. The results demonstrate that the proposed approach can significantly reduce both the transportation and GHG emission costs compared to the conventional facility-location model. This effort will be useful for decision makers and transportation planners in the analysis of network-wise impacts of traffic congestion and vehicle emission when deciding the locations of high demand facilities in urban areas.

Original languageEnglish
Pages (from-to)233-244
Number of pages12
JournalJournal of Environmental Engineering and Landscape Management
Volume24
Issue number4
DOIs
Publication statusPublished - 2016 Oct 1

Fingerprint

facility location
traffic congestion
Traffic congestion
heuristics
Gas emissions
Greenhouse gases
greenhouse gas
cost
Costs
urban area
public service
traffic emission
genetic algorithm
Retail stores
demand
Tabu search
Genetic algorithms
Mathematical models

Keywords

  • facility location model
  • genetic algorithm
  • logistics systems planning
  • memetic algorithm
  • meta-heuristic algorithm
  • tabu search algorithm
  • traffic congestion
  • vehicle GHG emission

ASJC Scopus subject areas

  • Environmental Engineering
  • Nature and Landscape Conservation
  • Management, Monitoring, Policy and Law

Cite this

Meta-heuristic approach for high-demand facility locations considering traffic congestion and greenhouse gas emission. / Hwang, Taesung; Lee, Minho; Lee, Chungwon; Kang, Seungmo.

In: Journal of Environmental Engineering and Landscape Management, Vol. 24, No. 4, 01.10.2016, p. 233-244.

Research output: Contribution to journalArticle

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