Solving the shortest route cut and fill problem using simulated annealing

Darrall Henderson, Diane E. Vaughan, Sheldon H. Jacobson, Ron R. Wakefield, Edward C. Sewell

Research output: Contribution to journalArticlepeer-review

Abstract

This paper introduces the shortest route cut and fill problem (SRCFP). The SRCFP is a NP-hard discrete optimization problem for leveling a construction project site, where the objective is to find a vehicle route that minimizes the total distance traveled by a single earthmoving vehicle between cut and fill locations. An optimal vehicle route is a route that minimizes the total haul distance that a single earthmoving vehicle travels. Simulated annealing algorithms are formulated to address the SRCFP. To assess the effectiveness of simulated annealing on the SRCFP, a greedy algorithm is constructed to compute an upper bound and the Held-Karp 1-tree lower bound is used to compute a lower bound. Extensive computational results are reported using several randomly generated instances of the SRCFP.

Original languageEnglish (US)
Pages (from-to)72-84
Number of pages13
JournalEuropean Journal of Operational Research
Volume145
Issue number1
DOIs
StatePublished - Feb 16 2003

Keywords

  • Heuristics
  • Local search algorithms
  • Shortest route problem
  • Simulated annealing
  • Traveling salesman problem

ASJC Scopus subject areas

  • General Computer Science
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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