This work deals with optimization methods for the selection of submarine pipeline routes, employed to carry the oil & gas from offshore platforms. The main motives are related to the assessment of constraint-handling techniques, an important issue in the application of genetic algorithms and other nature-inspired algorithms to such complex, real-world engineering problems. Several methods associated to the modeling and solution of the optimization problem are addressed, including: the geometrical parameterization of candidate routes; their encoding in the context of the genetic algorithm; and, especially, the incorporation into the objective function of the several design criteria involved in the route evaluation. Initially, we propose grouping the design criteria as either “soft” or “hard”, according to the practical consequences of their violation. Then, the latter criteria are associated to different constraint-handling techniques: the classical static penalty function method, and more advanced techniques such as the Adaptive Penalty Method, the ε-Constrained method, and the Ho-Shimizu technique. Case studies are presented to compare the performance of these methods, applied to actual offshore scenarios. The results indicate the importance of clearly characterizing feasible and infeasible solutions, according to the classification of design criteria as “soft” or “hard” respectively. They also indicate that the static penalty approach is not adequate, while the other techniques performed better, especially the ε-Constrained and the Ho-Shimizu methods. Finally, it is seen that the optimization tool may reduce the design time to assess an optimal route, providing accurate results, and minimizing the costs of installation and operation of submarine pipelines. 
Optimal design of submarine pipeline routes by genetic algorithm with different constraint handling techniques