Authors:
Botan M. Ahmad AL-Hadad
and
Michael Mawdesley
Affiliation:
University of Nottingham, United Kingdom
Keyword(s):
Highway alignment, Genetic algorithms, Optimization.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Evolutionary Multiobjective Optimization
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Soft Computing
Abstract:
This paper reports for the possibility of developing a genetic algorithm (GA) based technique model to optimize highway alignment. It suggests a novel technique to optimize a highway alignment in a three dimensional space. The technique considers station points to simultaneously configure both horizontal and vertical alignment rather than considering the existing conventional principles of design which deals with both alignments in two different stages and uses horizontal intersection points (HIP), vertical intersection points (VIP), tangents (T), curve radii (R), deflection angles (∆), grade values (± g %), and horizontal and vertical curve fittings to depict the horizontal and vertical alignments. The proposed method is expected to produce a global optimal or near optimal solution and also to reduce the number of highway alignment design elements required and consequently reduce the constraints imposed on alignment planning and design. The results obtained have good merits and enco
urage further investigations for better solutions.
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