Drilling path optimization by the particle swarm optimization algorithm with global convergence characteristics

Drilling path optimization by the particle swarm optimization algorithm with global convergence characteristics

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Article ID: iaor2009911
Country: United Kingdom
Volume: 46
Issue: 8
Start Page Number: 2299
End Page Number: 2311
Publication Date: Jan 2008
Journal: International Journal of Production Research
Authors: ,
Keywords: heuristics: ant systems
Abstract:

Drilling path optimization is one of the key problems in holes-machining. This paper presents a new approach to solve the drilling path optimization problem belonging to discrete space, based on the particle swarm optimization (PSO) algorithm. Since the standard PSO algorithm is not guaranteed to be global convergent or local convergent, based on the mathematical model, the algorithm is improved by adopting the method to generate the stop evolution particle once again to obtain the ability of convergence on the global optimization solution. Also, the operators are proposed by establishing the Order Exchange Unit (OEU) and the Order Exchange List (OEL) 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 convergence capability. Hence the new PSO can play a role in solving the problem of drilling path optimization.

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