Solving Customer Order Scheduling Problems with an Iterated Greedy Algorithm
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Publisher
Springer International Publishing
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https://link.springer.com/content/pdf/10.1007/978-3-031-24907-5_6
Reference10 articles.
1. Framinan, J. M., & Perez-Gonzalez, P. (2017). New approximate algorithms for the customer order scheduling problem with total completion time objective. Computers and Operations Research, 78, 181–192. https://doi.org/10.1016/j.cor.2016.09.010
2. Leung, J. Y. -T., Li, H., & Pinedo, M. (2005) Order scheduling in an environment with dedicated resources in parallel. Journal of Scheduling, 8(5), 355–386. https://doi.org/10.1007/s10951-005-2860-x
3. Zipfel, B., Neufeld, J. S., & Buscher, U. (2021). Customer order scheduling in an additive manufacturing environment. In A. Dolgui, A. Bernard, D. Lemoine, G. von Cieminski & Romero, D. (Eds.), Advances in production management systems. Artificial intelligence for sustainable and resilient production systems. APMS 2021. IFIP advances in information and communication technology (Vol. 633, pp. 101–109). Springer, Cham. https://doi.org/10.1007/978-3-030-85910-7_11
4. Sung, C. S., & Yoon, S. H. (1998). Minimizing total weighted completion time at a preassembly stage composed of two feeding machines. International Journal of Production Economics, 54(3), 247–255. https://doi.org/10.1016/S0925-5273(97)00151-5
5. Leung, J. Y. T., Lee, C., Ng, C., & Young, G. (2008). Preemptive multiprocessor order scheduling to minimize total weighted flowtime. European Journal of Operational Research, 190(1), 40–51. https://doi.org/10.1016/j.ejor.2007.05.052
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