Stochastic Optimal Haul-Route Searching Method Based on Genetic Algorithm and Simulation

This paper presents an advanced stochastic optimal earthmoving haul-route searching method (SOHS) that hybridizes the genetic algorithm (GA) and simulation, hence minimizing the equipment travel time and fuel consumption. It evaluates alternative haul routes and identifies global solution(s) exhaustively by simultaneously taking into account three-dimensional contour data, the dimensions of physical quantities concerned with equipments, and geological features of the job site surface under study. This study is of value to researchers because SOHS remarkably improves computational speed, reliability, and usability of existing methods. It is also of relevance to practitioners because SOHS provides an easy-to-use computerized tool that reduces the lengthy computations relative to data processing, GAs, and simulations. Two test cases verify the validity of the computational method.

• Record URL:
  https://doi.org/10.1061/(ASCE)CP.1943-5487.0000496
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/08873801
• Supplemental Notes:
  • © 2016 American Society of Civil Engineers.
• Authors:
  • Gwak, Han-Seong
  • Yi, Chang-Yong
  • Lee, Dong-Eun
• Publication Date: 2016-5

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 04015029
• Serial:
  • Journal of Computing in Civil Engineering
  • Volume: 30
  • Issue Number: 3
  • Publisher: American Society of Civil Engineers
  • ISSN: 0887-3801

Subject/Index Terms

• TRT Terms: Earthwork; Genetic algorithms; Haul distance; Optimization; Routes; Simulation; Stochastic processes
• Subject Areas: Freight Transportation; Planning and Forecasting;

Filing Info

• Accession Number: 01597329
• Record Type: Publication
• Files: TRIS, ASCE
• Created Date: Apr 27 2016 9:55AM