Application of a hybridized cuckoo search-genetic algorithm to path optimization for PCB holes drilling process

The drilling path optimization problem is a NP-hard combinatorial optimization problem. Due to complexity and exponential growth of solution space with respect to the problem size, drilling path optimization problem attracts a great interest among the academicians. In this paper, a hybrid algorithm cuckoo search with genetic algorithm (hybrid-CSGA) is applied to solve the path optimization problem for printed circuit board (PCB) holes drilling process. It is shown that hybrid-CSGA reaches the near-optimal solution much earlier than the CS and GA approach for small and large size problem instances. The computational experience conducted in this research indicates that the proposed method is robust, efficient, capable to find the best path for the PCB holes drilling path optimization problem.

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