A Global-Local Optimization Algorithm And Its Application In The Pile Bearing Capacity Inversion

The global optimization algorithm can search widely, but its local searchingability is poor, local optimization algorithm is on the contrary. A global?localoptimization algorithm, genetic algorithm?simplex, is presented in this paper,which takes the advantage of both global and local optimization algorithms.Afterwards this global?local optimization algorithm is applied in pile bearingcapacity inversion; furthermore an effective technical route is presented to aim atthe characteristic of the problem.Genetic algorithm is a global optimization algorithm that attracts muchattention, and has been used in many fields. The main procedure and existingshortcomings of this algorithm is analysised and summarized in this paper, thenthe divergence of simple genetic algorithm and the convergence of simple geneticalgorithm which adapts the elitist strategy are concisely proved, which can beeasily understand by engineering researcher. Taking advantages of searchingeffectively, implementing easily and combining properly of simplex, thepremature of genetic algorithm is overcame and the calculating efficiency ofgenetic algorithm is also improved by using simplex to enhance the searchingalility, to provide new models and to increase the variety of the population.Afterwards, numerical experiments are provided by seven testing functions thatcan rigorously examine the searching ability of algorithm in various aspects.Compared with several other global optimization algorithms, the searching abilityof genetic?simplex presented in this paper is verified.The CAPWAPC is a high strain dynamic testing method of pile bearingcapacity that is applied extensively. It provides forward program and suggestsusing manual try and error to inverse pile?soil model parameters. However, thismethod is not easily implemented and the inverse results depend on user'sempiricy. The detailed materials of CAPWAPC are also inavailable because oftechnocal security. The pile?soil model is analyzed and complete forwardformulas are given in this paper. Then, the genetic algorithm?simplex is appliedto the inversion of pile bearing capacity. Also an effective technical route, inwhich emprical influences can be avoided, is developed and correspendingsoftware is compiled. Considering too many parameters and time?comsuming...