Optimization Algorithm of Mine Ventilation Based on SA-IPSO

doi:10.16182/j.issn1004731x.joss.20-0403

Abstract

Abstract: A non-linear optimization mathematical model aiming at the minimum total power of the mine ventilation network is established, in which SA-IPSO algorithm is applied for the optimization. The mutation operation is introduced in the PSO algorithm, in which a new inertia weight is proposed and a new particle selection method is constructed to control the number of particles violating the constraints, and the ability of the PSO algorithm to find boundaries is improved. The constraint conditions of the mine ventilation law are transformed into the penalty term of the objective function. IPSO optimizes the objective function and uses SA to achieve the global optimum. The simulation experiment of Xintun Mine shows that the algorithm can reduce the total energy consumption of ventilation by 95.69Kw while the air volume can meet the demand.

Key words: mutation operation, inertia weight, constraint problem, improved particle swarm, penalty term, simulated annealing

CLC Number:

TP391
X936

Shao Liangshan, Wang Zhen, Li Changming. Optimization Algorithm of Mine Ventilation Based on SA-IPSO[J]. Journal of System Simulation, 2021, 33(9): 2085-2094.

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