Comparison of Single and Multi Objective Highway Alignment Optimization Algorithms

Highway alignment, the route of the road, is a factor in determining costs when designing roads. This article compares single- and multi-objective highway alignment optimization (HAO) algorithms currently in use. The authors note that these algorithms consider different highway alignment costs along with information about restricted land use (e.g., forests, wetlands, etc.). In single-objective HAO approaches, different highway alignment sensitive costs are formulated and added to obtain the total highway alignment costs. In the multi-objective optimization approach the highway alignment cost and restricted land use information are maintained separately and optimized simultaneously. Thus, the multi-objective HAO helps to yield a set of Pareto-optimal solution with trade-off between highway alignment cost and the restricted land use information. The authors determined that it is cumbersome to express the highway alignment and associated objectives in mathematical formulations as required in classical optimization techniques. Instead, both of the methods they considered use unconventional genetic algorithm (GA)-based optimization approaches. The authors use a real-world example (Harford County, Maryland) application to discuss the benefits and drawbacks of each HAO method. They conclude that developing a standardized computer program to prepare the GIS database according to the requirement of the algorithms may speed up preprocessing of the maps and database required to perform the optimizations. Although the multi-objective approach is newer, it offers great potential for highway design.

Language

  • English

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Filing Info

  • Accession Number: 01380340
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Aug 21 2012 8:50AM