ArticleBiomimetics (Basel, Switzerland)2026
Multi-Objective Airflow Distribution Design in Mine Ventilation Systems Based on Sensitivity Screening and an Improved Multi-Objective Sparrow Search Algorithm.
Article in Biomimetics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This study proposes a biomimetic multi-objective optimization framework for airflow distribution design in mine ventilation systems by integrating sensitivity screening with an improved multi-objective sparrow search algorithm (IMOSSA). The design problem is formulated with network-balance, critical branch airflow, fan-boundary, and adjustable-resistance constraints, while theoretical ventilation air power and pressure-drop disturbance are minimized as two conflicting objectives. Resistance-perturbation sensitivity analysis is used to identify high-impact adjustable branches and construct branch-specific search bounds, thereby forming a compact and physically feasible decision domain. Inspired by the foraging and vigilance behaviors of sparrow populations, IMOSSA is employed as a swarm-intelligence Pareto-search engine and integrates three strategies: chaotic opposition-based elite initialization to enhance initial population diversity, density-penalized external-archive guidance to maintain Pareto-front diversity, and stagnation-triggered differential-Cauchy perturbation to improve late-stage escape capability. ZDT and DTLZ benchmark functions verify the computational reliability of IMOSSA; in particular, on the multimodal ZDT4 function, IMOSSA achieves GD, IGD, and HV values of 0.0096, 0.0195, and 0.8479, respectively, indicating strong robustness in complex Pareto-front search. A mine ventilation network case further validates the engineering applicability of the proposed framework. For 13 adjustable branches, the compromise solution reduces model-computed ventilation air power from 313.61 kW to 281.11 kW, corresponding to a reduction of 10.36%, with a pressure-drop deviation of 354.15 Pa; the energy-priority solution further reduces the power to 256.91 kW, corresponding to a reduction of 18.08%. The results show that the proposed biomimetic multi-objective optimization framework can provide computable and interpretable Pareto decision support for airflow distribution design in mine ventilation systems.
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