Please use this identifier to cite or link to this item: https://doi.org/10.1109/CSO.2009.405
Title: Using hybrid particle swarm optimization for process planning problem
Authors: Wang, Y.F.
Zhang, Y.F. 
Fuh, J.Y.H. 
Issue Date: 2009
Citation: Wang, Y.F., Zhang, Y.F., Fuh, J.Y.H. (2009). Using hybrid particle swarm optimization for process planning problem. Proceedings of the 2009 International Joint Conference on Computational Sciences and Optimization, CSO 2009 1 : 304-308. ScholarBank@NUS Repository. https://doi.org/10.1109/CSO.2009.405
Abstract: In this paper, a hybrid particle swarm optimization (PSO) incorporating local search algorithm is reported to handle the process planning problem. From modeling perspective, the process planning problem is considered as deciding the operation methods, including selection of machine, tool and tool approach direction, and operation sequencing in a concurrent way, which is a non-deterministic polynomial-time (NP) hard combinatorial problem. To solve this discrete optimization problem, a hybrid PSO approach is proposed using a specific solution representation, update and search. The presented case study has shown the capability of the proposed algorithm to gain a good quality of solution. © 2009 IEEE.
Source Title: Proceedings of the 2009 International Joint Conference on Computational Sciences and Optimization, CSO 2009
URI: http://scholarbank.nus.edu.sg/handle/10635/73994
ISBN: 9780769536057
DOI: 10.1109/CSO.2009.405
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