A Multi-Objective Genetic Algorithm for Optimizing Highway Alignments

We develop a multi-objective approach to optimize 3-dimensional (3D) highway alignments using a genetic algorithm. Multi-objective genetic algorithms have been very popular for handling trade-offs among various objectives. The concept of Pareto optimally has been introduced in works and multi-objective genetic algorithms have been developed for this purpose. What we have found is that every problem is unique and there is no black box approach to implement multi-objective genetic algorithms in all problems. We implement the Pareto-optimality concept to develop a multi-objective genetic algorithm for the 3D highway alignment optimization problem on which we have worked for the last 10 years. We apply the multi-objective optimization approach to an example problem on which we had previously worked. The results suggest that the multi-objective approach has great promise for obtaining the best trade-off among various objectives to reach an optimal solution