Pipeline optimization using a novel hybrid algorithm combining front projection and the non-dominated sorting genetic algorithm-II (FP-NSGA-II)

In this paper, a procedure for minimizing the pumping power, the number of pumping stations and the total pipeline mass required for a pipeline project is presented using multiobjective optimization. Two and three-objective optimization cases were considered. The decision variables included the outer diameter, wall thickness, suction pressure and discharge pressure. A novel hybrid multiobjective optimization algorithm combining NSGA-II with a simple front prediction (FP-NSGA-II) is proposed to improve upon the performance NSGA-II. Then, the application of the proposed algorithm to a problem taken from the open literature is presented and analyzed. The resulting Pareto domain was ranked using a cost function. Results indicate that FP-NSGA-II improved significantly convergence, spread and number of non-dominated solutions for the determination of the optimal design for a specified pipeline problem.