Simultaneous Optimization of Horizontal and Vertical Alignments of Forest Roads Using Tabu Search

Abstract

We developed a forest road design model that simultaneously optimizes horizontal and vertical alignments of forest roads using a high resolution Digital Elevation Model (DEM). Once an initial horizontal alignment is established by locating a series of intersection points, the model generates alternative horizontal and vertical alignments and cross sections along the road prism. The model also estimates earthwork volume and construction and maintenance costs for given road alignments and their spatial locations. The model then optimizes road alignments based on construction and maintenance costs using Tabu Search, one of the modern heuristic techniques.

The model was applied to a part of Capitol Forest in Washington State, USA, where a high resolution DEM derived from LiDAR (Light Detection and Ranging) data was available. First, the program generated an initial horizontal alignment with the length of 827m and five horizontal curves based on manually selected intersection points. Then, the vertical alignment was optimized based on the initial horizontal alignment, which resulted in a total cost of $50,814, considering construction and maintenance costs. The optimized forest road alignment, whose horizontal and vertical alignments were simultaneously optimized during the search process, reduced the total cost and the road length by 36% and 19% compared to the initial horizontal alignment, respectively.

Keywords:

• Forest road alignment
• Forest road design
• Heuristic optimization technique
• High resolution DEM
• Tabu Search
• Washington State