DISTRIBUTED MONKEY ALGORITHM FOR OPTIMAL SENSOR PLACEMENT

The distributed monkey algorithm is established for the optimal sensor placement of multi-degree- of-freedom large structures. Firstly, the problem that the original monkey algorithm can only solve the problem of continuous variables is overcome by introducing the dual-structure coding method. Then, a new method is proposed that assigning large number of individual monkeys generated by the initialization to multi-group of monkeys in a specified way and performing the parallel search. Considering that the original monkey algorithm is able to step out local optimum while the harmony search algorithm has better local search capability, the two-step search algorithm is adopted based on the basic harmony search algorithm by collecting the preliminary optimum gotten by each group of monkeys as the original harmony memory to obtain the final sensor placement scheme. Finally, the parametric sensitivity analysis and the selection of sensor placement schemes are performed on the Dalian International Trade Mansion. The results show that the distributed monkey algorithm has better global search capability and it is applicable to the sensor placement of multiple-degree-of-freedom large structures.