@inproceedings{9e9cfb5e8a4344059fa2a523c1ce15a3,
title = "Stochastic models for an optimal blending of biomass under cost, quality and uncertainty considerations",
abstract = "Blending biomass materials of different physical or chemical properties provides an opportunity to passively adjust the quality of the feedstock to meet the specifications of the conversion platform. We propose a model which identifies the right mix of biomass to optimize the performance of the Thermochemical conversion process at the minimum cost. This is a chance-constraint programming (CCP) model which takes into account the stochastic nature of biomass availability and quality. The proposed CCP model takes as inputs the physical and chemical properties, and biomass availability. We use the sample average approximation (SAA) method to solve the problem. We develop a case study for South Carolina by using data provided by the Billion Ton Study. We conduct extensive numerical analysis to evaluate the quality of the solutions obtained.",
keywords = "Biomass, Chance-constraint optimization, Sample average approximation",
author = "Mowen Lu and Jiaqi Qian and Ek{\c s}ioǧlu, \{Sandra D.\} and Roni, \{Mohammad S.\}",
year = "2017",
language = "English",
series = "67th Annual Conference and Expo of the Institute of Industrial Engineers 2017",
publisher = "Institute of Industrial Engineers",
pages = "1103--1108",
editor = "Nembhard, \{Harriet B.\} and Katie Coperich and Elizabeth Cudney",
booktitle = "67th Annual Conference and Expo of the Institute of Industrial Engineers 2017",
note = "67th Annual Conference and Expo of the Institute of Industrial Engineers 2017 ; Conference date: 20-05-2017 Through 23-05-2017",
}