An improved ant colony algorithm enhances inspection path optimization in CMMs, suggesting higher efficiency and performance.
To address the disordered inspection paths and long inspection time encountered when coordinate measuring machines (CMMs) inspect free-formsurface parts, an improved ant colony algorithm was proposed to optimize the inspection path and thereby improve inspection efficiency. To enhance the optimization performance of the ant colony algorithm and overcome its shortcomings, such as low search speed and susceptibility to local optimal solutions, this work improves the initial pheromone distribution, pheromone evaporation factor, and pheromone update strategy and introduces a local search strategy. The experimental results revealed that the improved ant colony algorithm had strong search directionality in the early stages of iteration, higher search speed, and an enhanced ability to escape from local optimal solutions; the inspection paths of the free-form surface optimized by the improved ant colony algorithm were neat and aesthetically pleasing, and the inspection efficiency increased by up to 14.75%, 23.59%, and 34.21% compared with those of the classic ant colony algorithm, artificial bee colony algorithm, and genetic algorithm, respectively.
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Chen et al. (2025) studied this question.
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