Optimization Selection Model and its Genetic Algorithm for a Logistics Chain

There are several paths or nodes to be selected to form a useful and efficient logistics chain. But how to decide which path or node would be selected is an issue in the field of logistics planning and optimization. The issue can be described as mixed-integer programming. The model can be settled by some exact algorithm, such as the branch and bound method, or random-heuristic search method when the dimensions of the problem are small. But when the dimensions of the problem are large, the problem belongs to NP-complete problem. A genetic algorithm is designed to settle the model. The main impact facts of the algorithm, such as coding, representation of the data, population size, and fitness function, are analyzed.

• Record URL:
  • https://doi.org/10.1061/9780784413159.136
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784413159
• Supplemental Notes:
  • © 2013 American Society of Civil Engineers
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Ma, Xiaolai
  • Mao, Min
• Conference:
  • Fourth International Conference on Transportation Engineering
  • Location: Chengdu , China
  • Date: 2013-10-19 to 2013-10-20
• Publication Date: 2013-10

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 925-930
• Monograph Title: ICTE 2013: Safety, Speediness, Intelligence, Low-Carbon, Innovation

Subject/Index Terms

• TRT Terms: Freight transportation; Genetic algorithms; Logistics; Mixed integer programming; Optimization; Supply chain management
• Subject Areas: Freight Transportation; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01516756
• Record Type: Publication
• ISBN: 9780784413159
• Files: TRIS, ASCE
• Created Date: Mar 3 2014 10:52AM