Improved ant colony optimization algorithm and its application to solve pipe routing design

Abstract

Purpose As a kind of NP-hard combinatorial optimization problem, pipe routing design (PRD) is applied widely in modern industries. In the offshore oil and gas industry, a semi-submersible production platform is an important equipment for oil exploitation and production. PRD is one of the most key parts of the design of semi-submersible platform. This study aims to present an improved ant colony algorithm (IACO) to address PRD for the oil and gas treatment system when designing a semi-submersible production platform. Design/methodology/approach First, to simplify PRD problem, a novel mathematical model is built according to real constraints and rules. Then, IACO, which combines modified heuristic function, mutation mechanism and dynamical parameter mechanism, is introduced. Findings Based on a set of specific instances, experiments are carried out, and the experimental results show that the performance of IACO is better than that of two variants of ACO, especially in terms of the convergence speed and swarm diversity. Finally, IACO is used to solve PRD for the oil and gas treatment system of semi-submersible production platform. The simulation results, which include nine pipe paths, demonstrate the practicality and high-efficiency of IACO. Originality/value The main contribution of this study is the development of method for solving PRD of a semi-submersible production platform based on the novel mathematical model and the proposed IACO.