Cargo Transportation Path Optimization Based on Intelligent Algorithm

This paper analyzes the problem of cargo transportation optimization based on improved genetic algorithm and improved ant colony algorithm. The results show that genetic algorithm is better than ant colony algorithm in the calculation efficiency of genetic algorithm, the algorithm stability and the stability of the calculated results. On the other hand, ant colony algorithm is able to conduct an optimization path with "duplicate point", which cannot be realized by the genetic algorithm. These two kinds of intelligent algorithms are complementary in solving path optimization problems.

• Record URL:
  https://doi.org/10.1061/41139(387)496
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784411391
• Supplemental Notes:
  • © 2010 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Hao, Yuzhu
  • Huo, Zaiqiang
• Conference:
  • International Conference of Logistics Engineering and Management (ICLEM) 2010
  • Location: Chengdu , China
  • Date: 2010-10-8 to 2010-10-10
• Publication Date: 2010-9

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 3552-3559
• Monograph Title: ICLEM 2010: Logistics For Sustained Economic Development: Infrastructure, Information, Integration

Subject/Index Terms

• TRT Terms: Cargo handling; Freight transportation; Genetic algorithms; Logistics; Optimization; Stability analysis
• Uncontrolled Terms: Ant colony optimization
• Subject Areas: Aviation; Freight Transportation; Highways; Marine Transportation; Planning and Forecasting; Railroads; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01525595
• Record Type: Publication
• ISBN: 9780784411391
• Files: TRIS, ASCE
• Created Date: Nov 12 2013 1:53PM