Application of generalized perturbation theory to hill climbing-based optimization of material arrangement in beam...

In order to realize broad-range search in optimization problems of material selection and their arrangement in the design of Beam Shaping Assembly (BSA), a new method combining the generalized perturbation theory (GPT) to the hill climbing algorithm is proposed. In this method, all possible candidate solutions neighboring a current solution are thoroughly considered, and difference of each of these candidates from the current one in the objective function and the constraints is rapidly estimated by GPT. To examine the proposed method, a one-dimensional slab problem is treated with the diffusion equation. The proposed method with 13 different initial conditions is tested, and the solution satisfying all criteria is obtained in 9 cases. It is also demonstrated that the final material arrangement is not significantly dependent on the initial conditions. Through the present work, it is confirmed that our proposed algorithm has a potential to find excellent solution in the optimization problem of material arrangement in BSA.