A genetic algorithms simulation approach for the multi-attribute combinatorial dispatching decision problem
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Bibliographic InfoArticle provided by Elsevier in its journal European Journal of Operational Research.
Volume (Year): 176 (2007)
Issue (Month): 3 (February)
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- Pongcharoen, P. & Hicks, C. & Braiden, P. M. & Stewardson, D. J., 2002. "Determining optimum Genetic Algorithm parameters for scheduling the manufacturing and assembly of complex products," International Journal of Production Economics, Elsevier, vol. 78(3), pages 311-322, August.
- Rajendran, Chandrasekharan & Holthaus, Oliver, 1999. "A comparative study of dispatching rules in dynamic flowshops and jobshops," European Journal of Operational Research, Elsevier, vol. 116(1), pages 156-170, July.
- Azadivar, Farhad & Tompkins, George, 1999. "Simulation optimization with qualitative variables and structural model changes: A genetic algorithm approach," European Journal of Operational Research, Elsevier, vol. 113(1), pages 169-182, February.
- Petroni, Alberto & Rizzi, Antonio, 2002. "A fuzzy logic based methodology to rank shop floor dispatching rules," International Journal of Production Economics, Elsevier, vol. 76(1), pages 99-108, March.
- Sarper, H. & Henry, M. C., 1996. "Combinatorial evaluation of six dispatching rules in a dynamic two-machine flow shop," Omega, Elsevier, vol. 24(1), pages 73-81, February.
- Chiang, Tsung-Che & Fu, Li-Chen, 2009. "Using a family of critical ratio-based approaches to minimize the number of tardy jobs in the job shop with sequence dependent setup times," European Journal of Operational Research, Elsevier, vol. 196(1), pages 78-92, July.
- Branke, Juergen & Pickardt, Christoph W., 2011. "Evolutionary search for difficult problem instances to support the design of job shop dispatching rules," European Journal of Operational Research, Elsevier, vol. 212(1), pages 22-32, July.
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