Genetic algorithm-based pipeline layout for refrigeration plant rooms

Yu Shi; Lun Zhang

doi:10.1117/12.2684989

19 October 2023 Genetic algorithm-based pipeline layout for refrigeration plant rooms

Yu Shi, Lun Zhang

Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 127093C (2023) https://doi.org/10.1117/12.2684989
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China

Abstract

For the existing refrigeration room design is mostly manual design, low efficiency, in the design of complex refrigeration room, it is difficult to determine the optimal path problem. For this reason, this study uses a genetic algorithm for the automatic arrangement of pipeline orientation with the basic idea of reducing system resistance and rational use of space. The algorithm models the refrigeration plant room, encodes the coordinate points and judges the merit of the route based on the path of the pipeline, the number of elbows and the compactness of the pipeline arrangement and avoidance of obstacles as evaluation indicators. The results, verified by arithmetic examples, show that the method is practical and feasible in the design of pipelines for refrigeration plant rooms. Combining the AI algorithm with the traditional industry design phase helps to change the traditional design model and improve design efficiency, as well as solving the problem of manual difficulty in determining the optimal pipeline route in complex situations. The algorithm, when studied in more depth, can assist in the path planning of a single pipeline in complex situations and has good prospects for assisting in the design of large complex refrigeration plant rooms.

Citation Download Citation

Yu Shi and Lun Zhang "Genetic algorithm-based pipeline layout for refrigeration plant rooms", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 127093C (19 October 2023); https://doi.org/10.1117/12.2684989

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