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A novel genetic algorithm based method for solving continuous nonlinear optimization problems through subdividing and labeling. <i>Measurement</i>, <i>115</i>, 27–38. <a href=\"https://doi.org/10.1016/j.measurement.2017.09.034\">https://doi.org/10.1016/j.measurement.2017.09.034</a>","bibtex":"@article{Esmaelian_Tavana_Santos-Arteaga_Vali_2018, title={A novel genetic algorithm based method for solving continuous nonlinear optimization problems through subdividing and labeling}, volume={115}, DOI={<a href=\"https://doi.org/10.1016/j.measurement.2017.09.034\">10.1016/j.measurement.2017.09.034</a>}, journal={Measurement}, publisher={Elsevier BV}, author={Esmaelian, Majid and Tavana, Madjid and Santos-Arteaga, Francisco J. and Vali, Masoumeh}, year={2018}, pages={27–38} }","mla":"Esmaelian, Majid, et al. “A Novel Genetic Algorithm Based Method for Solving Continuous Nonlinear Optimization Problems through Subdividing and Labeling.” <i>Measurement</i>, vol. 115, Elsevier BV, 2018, pp. 27–38, doi:<a href=\"https://doi.org/10.1016/j.measurement.2017.09.034\">10.1016/j.measurement.2017.09.034</a>.","short":"M. 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