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By setting up the 'point milling process-TSPPC' model, this study firstly is to further discreteness the point milling process and then successfully transforms it into a traveling salesman problem with precedence constraints through setting the tabu list to record manufacturing procedures. Based on characteristics of the constraints, the tabu list is used to further expand the Bee Colony algorithm and get the Dynamic Tabu Artificial Bee Colony algorithm (DTABC-algorithm) which can dynamically update the solution space. The DTABC-algorithm is used to solve the 'point milling process-TSPWTR' model. By testing, not only the 'point milling process-TSPPC' model can effectively simplify the problem of point milling process, but also the DTABC-algorithm can show outstanding properties through the solving process.

Hole Machining Path Planning Optimization Based on Dynamic Tabu Artificial Bee Colony Algorithm