An Effective Genetic Algorithm for Multi-objective IPPS with Various Flexibilities in Process Planning
Author:
Publisher
Springer Berlin Heidelberg
Link
http://link.springer.com/content/pdf/10.1007/978-3-662-55305-3_15
Reference13 articles.
1. Li XY, Gao L, Li WD (2012) Application of game theory based hybrid algorithm for multi-objective integrated process planning and scheduling. Expert Syst Appl 39:288–297
2. Li XY, Gao L, Zhang CY, Shao XY (2010) A review on integrated process planning and scheduling. Int J Manuf Res 5:161–180
3. Guo YW, Li WD, Mileham AR, Owen GW (2009) Applications of particle swarm optimisation in integrated process planning and scheduling. Robot Comput-Integr Manuf 25:280–288
4. Li XY, Gao L, Wen XY (2013) Application of an efficient modified particle swarm optimization algorithm for process planning. Int J Adv Manuf Technol 67:1355–1369
5. Li WD, Ong SK, Nee AYC (2002) Hybrid genetic algorithm and simulated annealing approach for the optimization of process plans for prismatic parts. Int J Prod Res 40:1899–1922
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