Please use this identifier to cite or link to this item: https://doi.org/10.1080/00207543.2011.571459
Title: A hybrid particle swarm based method for process planning optimisation
Authors: Wang, Y.F.
Zhang, Y.F. 
Fuh, J.Y.H. 
Keywords: combinatorial optimisation
computer-aided process planning
local search
operation selection
operation sequencing
particle swarm optimisation
Issue Date: 1-Jan-2012
Source: Wang, Y.F., Zhang, Y.F., Fuh, J.Y.H. (2012-01-01). A hybrid particle swarm based method for process planning optimisation. International Journal of Production Research 50 (1) : 277-292. ScholarBank@NUS Repository. https://doi.org/10.1080/00207543.2011.571459
Abstract: A process planning (PP) problem is defined as to determine a set of operation-methods (machine, tool, and set-up configuration) that can convert the given stock to the designed part. Essentially, the PP problem involves the simultaneous decision making of two tasks: operation-method selection and sequencing. This is a combinatorial optimisation problem and it is difficult to find the best solution in a reasonable amount of time. In this article, an optimisation approach based on particle swarm optimisation (PSO) is proposed to solve the PP problem. Due to the characteristic of discrete process planning solution space and the continuous nature of the original PSO, a novel solution representation scheme is introduced for the application of PSO in solving the PP problem. Moreover, two kinds of local search algorithms are incorporated and interweaved with PSO evolution to improve the best solution in each generation. The numerical experiments and analysis have demonstrated that the proposed algorithm is capable of gaining a good quality solution in an efficient way. © 2012 Copyright Taylor and Francis Group, LLC.
Source Title: International Journal of Production Research
URI: http://scholarbank.nus.edu.sg/handle/10635/54278
ISSN: 00207543
DOI: 10.1080/00207543.2011.571459
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