Synergistic optimization of power matching and layout for fracturing–drilling equipment in extremely limited spaces via a hybrid GA–SA algorithm

Abstract Fracturing operations for thick-roof control in underground coal mines—especially at the Hetaoyu Coal Mine in the Ordos Basin—are frequently restricted to extremely constrained workspaces (approximately 5,460 m $$^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mmultiscripts> <mml:mrow/> <mml:mrow/> <mml:mn>2</mml:mn> </mml:mmultiscripts> </mml:math> ). Under such conditions, conventional experience-based planning often fails to simultaneously satisfy safety clearances, power-demand matching, and workflow efficiency. This paper proposes a synergistic power–layout optimization framework for fracturing–drilling equipment in minimal-area sites. First, a power–area coupling model is established to map functional power requirements to explicit spatial–geometric constraints. Second, a multi-objective optimization model is formulated to maximize site utilization while minimizing logistics costs and the center-of-mass (CoM) offset to enhance foundation stability. Third, a hybrid Genetic Algorithm–Simulated Annealing (GA–SA) algorithm is developed to solve the resulting nonlinear and highly constrained layout problem. Results show that the proposed GA–SA approach converges 31.7% faster than a standard GA. The optimized layout achieves 85.3% site utilization, limits the CoM offset to 1.23 m, and incorporates a dedicated fracturing operation lane to support high-pressure pumping operations. The proposed framework provides a quantitative and practical basis for safe, efficient drilling–fracturing integration in geotechnically sensitive sites with severely limited available area.