Abstract
According to the idea of wading across the stream by feeling the way, a kind of fast efficient random optimization algorithm is proposed. The wading across stream algorithm (WSA) acts as a solution as a start point, then searches several random solutions near the start point, and finds the best of these solutions. This best solution is taken as the next start point, and then several random solutions near this start point are searched, and so on. For solving continuous optimization problem, the improved wading across stream algorithm (IWSA) gradually shrinks the search space. The experimental results of some classic benchmark functions show that the proposed optimization algorithms improve extraordinarily the convergence velocity and precision. For solving the travelling salesman problem, the improved method selected the best of the initial solution as the start solution. To search the neighbourhood trial solution, four strategies are proposed. It is proved that reversal strategy is a simple and effective algorithm.
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