On Bayesian Approach to Grillage Optimization

In this paper, a new simplified version of the Bayesian Approach to coordinate global optimization (BAcoor) is compared with the well-known algorithms. BAcoor is a method of multi-dimensional optimization by applying a sequence of one-dimensional global optimizers starting from the best points obtained by previous one-dimensional optimization. The globality of one-dimension search is controlled by the only parameter. The new element is that observation points are defined by explicit formulas. In other similar methods this is performed by some numerical techniques that minimize the risk functions. The efficiency of suggested method is investigated and compared with other methods by solving a real-life civil engineering global optimization problem of pile placement schemes in grillage-type foundations. This problem is a good benchmark, because the minimal value of the objective function is known so the optimization error can be defined exactly.