Abstract:

Reliability analysis methods based on probability is proposed for analyzing slope stability to overcome the shortcomings caused by using safety factor as the standard of slope appraisal. For each given slip surface, an optimization model is suggested combined with Lagrange multiplier method. Genetic algorithm (GA) is adopted to search for the key slip surface, and a fitness function is proposed. According to the disadvantages of standard GA, the global and local research abilities can’t be controlled in the optimization process; the method of determining the best individual in offspring is improved, and the probabilities of crossover and mutation are adjusted dynamically guided by the increment of diverse characteristic value to assure population diversity and search validity. The results show that the search ability and convergence speed are improved, and the global optimal solution is guaranteed by the proposed method; the method is suitable for analyzing the reliability of slope stability with simple pretreatment; computational complexity of GA can be reduced greatly and much calculation time can be saved if computational model of reliability index is pre-optimized before GA performance.

Key words: slope reliability, optimization model, improved genetic algorithm, dynamic adjustment