By Topic

Fuzzy optimization for a batch simultaneous saccharification and co-fermentation process by hybrid differential evolution

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ming-Liang Chen ; Chem. Eng. Dept., Wu Feng Univ., Chiayi, Taiwan ; Wang, F.

The crisp and fuzzy optimization approaches were introduced to design an optimal temperature control policy for a batch process of simultaneous saccharification and cofermentation (SSCF) to produce ethanol from lignocellulose using the enzymes and the recombinant strain Saccharomyces yeast 1400 (pLNH33). The goal of the optimal design herein is to find the optimal temperature, initial lignocellulosic concentration, and fermentation time that maximize the ethanol productivity under the constraints of follow-up separation specifications. The interactive crisp and fuzzy optimization methods towards were respectively applied to solve the trade-off optimization problems in order to obtain a compromised design. The fuzzy goal attainment approach can more flexibly obtain a comprehensive design in comparison to the crisp optimization. Both crisp and fuzzy optimization could be efficiently solved by hybrid differential evolution.

Published in:

Evolutionary Computation (CEC), 2012 IEEE Congress on

Date of Conference:

10-15 June 2012