Journal Article10.1016/j.knosys.2021.107846
Improved dynamic adaptive ant colony optimization algorithm to solve pipe routing design
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TL;DR: In this paper , an improved dynamic adaptive ACO (IDAACO) is proposed to solve the pipe routing design problem for semi-submersible production platform in oil and gas industry.
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Abstract: With the purpose of finding a satisfactory pipe path between the starting point and target point, pipe routing design (PRD) has been applied in many industry fields. The research of two-dimensional PRD is the foundation of solving complex RPD problems, and has widely applications in factory layout, facilities installation, and so on. The ant colony optimization (ACO) algorithm is one of the most widely used approaches to solve PRD. However, the traditional ACO has drawbacks such as slow convergence speed, easy to fall into local optimum and low efficiency. In this study, an improved dynamic adaptive ACO (IDAACO) is proposed. The IDAACO includes four novel mechanisms which are the heuristic strategy with direction information, adaptive pseudorandom transfer strategy, improved local pheromone updating mechanism and improved global pheromone updating mechanism. Then, a series of experiments are carried out to verify the effectiveness of the four proposed mechanisms included by IDAACO. Subsequently, the IDAACO is compared with several existing approaches for solving PRD, and the experimental results confirm the advantages of IDAACO in terms of the practicality and high-efficiency. Finally, the IDAACO is used to solve the PRD problem for semi-submersible production platform in oil and gas industry.
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Citations
A mixing algorithm of ACO and ABC for solving path planning of mobile robot
TL;DR: This study proposes IACO-IABC, a hybrid algorithm combining ACO and ABC, to improve path planning efficiency for mobile robots. IACO-IABC enhances steering efficiency, exploitation of optimal solutions, and path optimization, outperforming traditional ACO and other intelligent search algorithms by 166.77-483.33% in path turn times.
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