Abstract：Water Wave Optimization (WWO) is a new kind of swarm intelligence algorithm inspired by the shallow water wave theory.Less control parameters,a small population size,easy implementation and small computational overheads,it also has disadvantages： less strong local search ability,slow convergence speed and so on.First,through the waves in the execution of global and local search optimization algorithm for requirements based on the analysis of the control parameters.improved water wave optimization algorithm used the adaptive adjustment strategy to adjust the control parameters； Finally,for the improved algorithm and including original WWO、SCA、DA,these four kinds of algorithms on 10 standard test functions optimization performance simulation experiment.Results show that the proposed strategy to effectively enhance the water waves to optimize the overall performance of the algorithm,in both the convergence accuracy and convergence speed,improved water wave algorithm,compared with other three kinds of algorithm optimization results are more stable.
2018, Vol. 39 
