Data-driven individual and joint chance-constrained optimization via kernel smoothing

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Bruno A. Calfa, Ignacio E. Grossmann, Anshul Agarwal, Scott J. Bury, John M. Wassick

Published: 2015, Last Modified: 14 May 2025Comput. Chem. Eng. 2015EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•Reformulation of individual and joint chance constraints using kernel smoothing.•Method to calculate the divergence tolerance based on kernel smoothing estimation.•Initialization scheme for joint chance-constrained problems.•Application in production planning with variability in production rates.