Abstract: The concrete structure is often degraded and damaged due to insufficient durability. In order to realize rapid and accurate determination of the optimization plan for concrete mix ratio, an LSSVMNSGAⅡ algorithm is established by selecting the frost resistance(dynamic elastic modulus) and antipermeability(chloride ion permeability coefficient) of main indices of concrete durability of a tunnel project in Jilin as study targets. The highprecision prediction of the concrete dynamic elastic modulus and durability index of chloride ion permeability coefficient is realized by using the least squares support vector machine (LSSVM) model based on raw materials and mix ratio. The regression prediction function is used as the fitness function and the constraint conditions of raw materials and mix ratio are established considering specifications and project requirements, and based on which the multiobjective optimization is achieved by NSGAⅡ. The results show that: (1) The prediction precision of the method mentioned above is high. (2) The targeted optimization values of concrete mix ratio can be obtained by regression function obtained and NSGAⅡ algorithm. (3) The performance of concrete prepared can meet relevant specifications and project requirements, and conforms to the actual conditions of the project. The results indicate the intelligence and precision of the model in the multiobjective optimization of concrete mix ratio.

Key words: tunnel, concrete durability, frost resistance, antipermeability; LSSVM, multiobjective mix ratio optimization, NSGAⅡ algorithm