A survey of pipe routing design

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.

Download Full-text

Improved dynamic adaptive ant colony optimization algorithm to solve pipe routing design

Knowledge-Based Systems ◽

10.1016/j.knosys.2021.107846 ◽

2021 ◽

pp. 107846

Author(s):

Chao Liu ◽

Lei Wu ◽

Xiaodong Huang ◽

Wensheng Xiao

Keyword(s):

Ant Colony Optimization ◽

Optimization Algorithm ◽

Ant Colony ◽

Ant Colony Optimization Algorithm ◽

Routing Design ◽

Pipe Routing

Download Full-text

A method based on PSO for pipe routing design

2016 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER) ◽

10.1109/cyber.2016.7574862 ◽

2016 ◽

Cited By ~ 1

Author(s):

Changtao Wang ◽

Liangliang Sun ◽

Xiaotong Sun ◽

Tiancheng Yuan

Keyword(s):

Routing Design ◽

Pipe Routing

Download Full-text

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

Assembly Automation ◽

10.1108/aa-02-2018-022 ◽

2019 ◽

Vol 39 (1) ◽

pp. 45-57 ◽

Cited By ~ 4

Author(s):

Lei Wu ◽

Xue Tian ◽

Hongyan Wang ◽

Qi Liu ◽

Wensheng Xiao

Keyword(s):

Mathematical Model ◽

Ant Colony Algorithm ◽

Oil And Gas ◽

Ant Colony ◽

Treatment System ◽

Gas Treatment ◽

Content Type ◽

Production Platform ◽

Routing Design ◽

Pipe Routing

PurposeAs 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/approachFirst, 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.FindingsBased 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/valueThe 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.

Download Full-text