Single-pipe layout method based on intelligent optimization hybrid algorithm

By integrating intelligent optimization methods that combine ant colony, A*, and artificial bee colony algorithms, the complexity of single-pipeline layout in FPSO oil and gas processing systems has been solved, achieving efficient and accurate pipeline planning, reducing costs and extending the design cycle.

CN121580565BActive Publication Date: 2026-05-26QINGDAO UNIV OF SCI & TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
QINGDAO UNIV OF SCI & TECH
Filing Date
2026-01-27
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

Existing technologies struggle to achieve efficient and precise single-pipeline layouts in FPSO oil and gas processing systems. Traditional manual layouts are highly subjective, and single intelligent algorithms have slow convergence speeds or are prone to getting stuck in local optima. Existing technologies fail to fully integrate the advantages of multiple algorithms, resulting in problems such as long design cycles, high costs, and pipeline interference.

Method used

A single-pipeline layout method based on intelligent optimization hybrid algorithm is adopted, which integrates ant colony algorithm, A* algorithm and artificial bee colony algorithm. The ant colony is divided into A* ants, leader ants, follower ants and scout ants. The path planning is optimized by combining directional heuristic search, multi-factor evaluation function, dynamic adaptive inertia weight and global pheromone update strategy.

Benefits of technology

It enables efficient and precise pipeline layout in complex three-dimensional space, reduces pipeline length and number of bends, lowers construction and operation costs, shortens design cycle, and improves pipeline operation stability and adaptability.

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Abstract

This invention relates to the field of pipeline layout technology, specifically to a single-pipeline layout method based on an intelligent optimization hybrid algorithm. Based on a pipeline layout mathematical model and considering the engineering constraints of oil and gas processing system pipeline layout, this application proposes an intelligent optimization hybrid algorithm that integrates the A* algorithm and artificial bee colony algorithm to address the shortcomings of the ant colony algorithm, such as slow convergence, premature convergence, and susceptibility to local optima. The ant colony is divided into four types with different working mechanisms: A* ants, leader ants, follower ants, and scout ants. A* ants improve the ant colony search speed, leader ants and follower ants enhance the ant colony search breadth, and scout ants further enhance the ant colony search depth.
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Citation Information

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