Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICCA.2010.5524365
Title: A PSO-based multi-objective optimization approach to the integration of process planning and scheduling
Authors: Wang, Y.F.
Zhang, Y.F. 
Fuh, J.Y.H. 
Issue Date: 2010
Source: Wang, Y.F.,Zhang, Y.F.,Fuh, J.Y.H. (2010). A PSO-based multi-objective optimization approach to the integration of process planning and scheduling. 2010 8th IEEE International Conference on Control and Automation, ICCA 2010 : 614-619. ScholarBank@NUS Repository. https://doi.org/10.1109/ICCA.2010.5524365
Abstract: This paper has presented a particle swarm optimization (PSO) based approach to handle a multi-objective integrated process planning and scheduling problem. The aim is to find a set of high-quality trade-off solutions. This is a combinatorial optimization problem with substantially large solution space, suggesting that it is highly difficult to find the best solutions with the exact search method. To account for it, a PSO-based algorithm is proposed by fully utilizing the capability of the exploration search and fast convergence. To fit the continuous PSO in the discrete modeled problem, a novel solution representation is introduced in the algorithm. Moreover, to improve the solution quality, a local search algorithm is used to perform on the stored elite solutions, which would facilitate the exploitation search in the regions with promising solutions. The numerical experiments have been performed to demonstrate the effectiveness of the proposed algorithm. © 2010 IEEE.
Source Title: 2010 8th IEEE International Conference on Control and Automation, ICCA 2010
URI: http://scholarbank.nus.edu.sg/handle/10635/73087
ISBN: 9781424451951
DOI: 10.1109/ICCA.2010.5524365
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