Displacement back analysis for underground engineering based on immunized continuous ant colony optimization

Abstract

The objective function of displacement back analysis for rock parameters in underground engineering is a very complicated nonlinear multiple hump function. The global optimization method can solve this problem very well. However, many numerical simulations must be performed during the optimization process, which is very time consuming. Therefore, it is important to improve the computational efficiency of optimization back analysis. To improve optimization back analysis, a new global optimization, immunized continuous ant colony optimization, is proposed. This is an improved continuous ant colony optimization using the basic principles of an artificial immune system and evolutionary algorithm. Based on this new global optimization, a new displacement optimization back analysis for rock parameters is proposed. The computational performance of the new back analysis is verified through a numerical example and a real engineering example. The results show that this new method can be used to obtain suitable parameters of rock mass with higher accuracy and less effort than previous methods. Moreover, the new back analysis is very robust.

Keywords:

• displacement back analysis
• complicated nonlinear optimization
• global optimization
• computing efficiency
• immunized continuous ant colony optimization

Disclosure statement

No potential conflict of interest was reported by the author.

Funding

Financial support from the Fundamental Research Funds for the Central Universities [grant nos 2014B17814, 2014B04914 and 2014B07014] is gratefully acknowledged.