Chemical Safety Inspection Path Optimization Problems Using Improved Multi-Objective Discrete Growth Optimization Algorithm DOI Open Access

Shanshan Luo,

Qiang Liu, Xiwang Guo

et al.

Processes, Journal Year: 2025, Volume and Issue: 13(5), P. 1445 - 1445

Published: May 9, 2025

Robot path planning plays a critical role in enhancing the efficiency and accuracy of inspections ultimately contributes to safety chemical production. In particular, performance robot inspection is influenced by amount gas leakage length. this study, multi-objective optimization model constructed that considers minimizing length maximizing detection sensitivity. To address model, an improved discrete growth algorithm proposed, which adopts operators meet solution requirements adaptive leader selection strategy further improve performance. Finally, numerical computations simulation experiments are conducted validate feasibility proposed method for planning. The results demonstrate outperforms particle swarm optimization, non-dominated sorting genetic algorithm-II, gray wolf terms convergence distribution uniformity. Moreover, it can provide better solutions multiple references practical applications.

Language: Английский

Chemical Safety Inspection Path Optimization Problems Using Improved Multi-Objective Discrete Growth Optimization Algorithm DOI Open Access

Shanshan Luo,

Qiang Liu, Xiwang Guo

et al.

Processes, Journal Year: 2025, Volume and Issue: 13(5), P. 1445 - 1445

Published: May 9, 2025

Robot path planning plays a critical role in enhancing the efficiency and accuracy of inspections ultimately contributes to safety chemical production. In particular, performance robot inspection is influenced by amount gas leakage length. this study, multi-objective optimization model constructed that considers minimizing length maximizing detection sensitivity. To address model, an improved discrete growth algorithm proposed, which adopts operators meet solution requirements adaptive leader selection strategy further improve performance. Finally, numerical computations simulation experiments are conducted validate feasibility proposed method for planning. The results demonstrate outperforms particle swarm optimization, non-dominated sorting genetic algorithm-II, gray wolf terms convergence distribution uniformity. Moreover, it can provide better solutions multiple references practical applications.

Language: Английский

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