
Drilling path optimization is the key problem in holes machining. This paper presents a swarm intelligent approach based on the particle swarm optimization (PSO) algorithm for solving the drilling path optimization problem. Because the standard PSO algorithm is not guaranteed to be global convergence or local convergence, the algorithm is improved by adopting the method of generating the stop evolution particle over again to get the ability of convergence on the global optimization solution. And the operators are improved by establishing the order exchange unit and the order exchange list to satisfy the need of integer coding in drilling path optimization. The experimentations indicate that the improved algorithm has the characteristics of easy realization, fast convergence speed, and better global converging capability. Hence the new PSO can play a role in solving the problem of drilling path optimization.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 19 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
