Multi-objective bilevel construction material transportation scheduling in large-scale construction projects under a fuzzy random environment

This paper investigates a transportation scheduling problem in large-scale construction projects under a fuzzy random environment. The problem is formulated as a fuzzy, random multi-objective bilevel optimization model where the construction company decides the transportation quantities from every source to every destination according to the criterion of minimizing total transportation cost and transportation time on the upper level, while the transportation agencies choose their transportation routes such that the total travel cost is minimized on the lower level. Specifically, the authors model both travel time and travel cost as triangular fuzzy random variables. Then the multi-objective bilevel adaptive particle swarm optimization algorithm is proposed to solve the model. Finally, a case study of transportation scheduling for the Shuibuya Hydropower Project in China is used as a real world example to demonstrate the practicality and efficiency of the optimization model and algorithm.

• Record URL:
  • https://doi.org/10.1080/03081060.2013.798486
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/1767712
• Supplemental Notes:
  • Abstract reprinted with permission from Taylor & Francis
• Authors:
  • Xu, Jiuping
  • Gang, Jun
• Publication Date: 2013-6

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 352-376
• Serial:
  • Transportation Planning and Technology
  • Volume: 36
  • Issue Number: 4
  • Publisher: Taylor & Francis
  • ISSN: 0308-1060
  • Serial URL: https://www.tandfonline.com/toc/gtpt20/current

Subject/Index Terms

• TRT Terms: Building materials; Construction projects; Construction scheduling; Productivity; Travel costs; Travel time
• Geographic Terms: China
• Subject Areas: Construction; Freight Transportation; I70: Traffic and Transport;

Filing Info

• Accession Number: 01486677
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 15 2013 10:05AM