Adaptive neighborhood method & GA for solving the vacancy route optimization of machining

The mathematical model of vacancy course path optimization of laser machining is built and changed to the travelling salesman problem (TSP). The Nearest Neighbor (NN) is modified to Adaptive Neighborhood Method (ANM). In ANM one mimics the traveller whose rule of thumb is not always to go next to the nearest asyetunvisited location. The next city is randomly selected from the unvisited cities in adaptive neighborhood. While solving the TSP, ANM is used to create the initial population at first, then iterations are done through selection, cross and mutation operation. In selection, the proposed algorithm only keep 90% samples from the previous generation, the remained agents are supplied by the new sample created by ANM. The results show that the algorithm shortens vacancy course in laser machining and the manufacturing efficiency is improved.

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