Ship Pipe Routing Design Using the ACO with Iterative Pheromone Updating

Abstract

Ship pipe routing design (SPRD) that belongs to non-deterministic polynomial (NP)-hard problem concerns minimizing the cost of pipe material while satisfying constraints and avoiding obstacles. Currently, this total solution mainly depends on human experts. The stochastic search algorithms suitable for computer technology provide the opportunity to automate and optimize it. The Ant Colony Optimization (ACO) is an effective metaheuristic and stochastic search technique to solve combinatorial optimization problems by using principle of pheromone information. Based on ACO, the method of ant colony algorithm with iterative pheromone updating is first proposed to solve ship pipeline routing in three-dimensional space. Simulation results show that the new updating approach of pheromone is feasible and effective. Mean-while, the performance and computer processing time of the proposed algorithm outperform the original ACO used to generate SPRD solutions.