In recent years, there has been a growing need to develop and delineate algorithms that quickly provideoptimized highway alignments. The matter is very complex since it is dominated by several factors andengineers have to achieve different and relevant targets (such as minimization of construction and earthworkcosts, compliance with environmental and right-of-way constraints, maximization of safety and comfort forusers, conformity with geometric standards). The possible solutions of this problem are clearly infinite andonly modern artificial intelligence techniques can really simplify and speed up the highway design process.In this study a search algorithm, based on a Swarm Artificial Intelligence technique (Particle SwarmOptimization method), to optimize highway 3-dimensional alignments, considering also environmentalconstraints, is proposed. This algorithm pertains to the minimization of a particular cost function, made up ofdifferent kinds of construction costs and some penalties, related to geometric and environmental constraints(geomorphologic, hydraulic and seismic constraints) and useful to avoid and discard incorrect alignments.Some specific operators, derived from Genetic Algorithms (GAs), were also introduced in the model forimproving its efficiency and correcting inappropriate solutions.To test the model efficiency, through the MatLab © software, an original script has been developed. Thetopography of the study area was reproduced through a particular Digital Terrain Model (DTM)representation.
|Number of pages||18|
|Journal||ADVANCES IN TRANSPORTATION STUDIES|
|Publication status||Published - 2013|
All Science Journal Classification (ASJC) codes
- Civil and Structural Engineering
- Automotive Engineering
- Safety, Risk, Reliability and Quality