Research on Adaptive Random Search Algorithm Based on Metropolis Criterion
Jiang Hui-b · Science and Technology of West China · 2015
Random search algorithm is an extremely simple optimization method, which has a poor effectiveness and limited computing range. To solve these problems, we put forward a search strategy of adaptive optimization,using the location of the current optimal point and the evolutionary path of current iteration to adjust the search direction and step length of algorithm constantly during optimization search, improving the searching efficiency.At the same time we used the rule of Metropolis in the simulated annealing algorithm, to improve the global search ability by both optimal solutions and deteriorative solutions. Then we used the MATLAB to simulate and comparatively analyzed it with traditional random algorithm. The results showed that the proposed algorithm in this paper has efficient optimization computing ability, and can be applied to optimization design in the field of engineering.