The multi-hole operation is a frequently used process in an industry. Owing to the escalating demand for reducing the production cost and time, it is inevitable for any manufacturing industry to develop an optimistic process plan. This research work mainly focuses on developing a novel combinatorial meta-heuristic hybrid technique for solving the proposed multi-hole drill sequencing problem. The integrated genetic and simulated annealing algorithm is hereby proposed and tested against assorted complex case study problems. From the results, it is evident that the proposed technique is superior in all aspects exceeding the reported optimum values. Also, this new technique consistently outperformed well with higher levels of precision and this stored data will aid the computer-aided process planning mechanism to perform well through machine learning.

中文翻译：

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使用混合组合 IGSA 算法优化多孔钻孔的机器学习

多孔操作是工业中经常使用的工艺。由于降低生产成本和时间的需求不断升级，任何制造行业都不可避免地制定了乐观的工艺计划。这项研究工作主要集中在开发一种新的组合元启发式混合技术，以解决所提出的多孔钻孔排序问题。特此提出集成遗传和模拟退火算法，并针对各种复杂的案例研究问题进行测试。从结果来看，很明显，所提出的技术在所有方面都优于报告的最佳值。此外，这种新技术在精度更高的情况下始终表现出色，并且这些存储的数据将有助于计算机辅助过程规划机制通过机器学习表现良好。