Green fuel is growing in popularity in recent years. Bio-reactive waste converted to green fuel through
anaerobic digestion technology. The performance of biogas unit has been optimized and formulated as
interval programming problems as function of inlet feed rate, retention time fermentation temperature and
pH. A new treatment for solving the interval nonlinear programming problem (INPP) is discussed. All the
intervals in the INPP are replaced by new variables. This the modified nonlinear programming problem
(MIPP). We presented three hybrid evolutionary algorithms (EAs) which are chaotic genetic algorithm
(CGA), chaotic particle swarm optimization (CPSO) and chaotic firefly algorithm (CFA) to solve MIPP. The
Karush–Kuhn–Tucker (KKT) conditions for MIPP are gotten. These equations are solved as algebraic
equations. Its solutions may be represented as a function of new variables to get the stability set of first
kind. The staring points in EAs is gotten by the Newton method. Finally, the comparison between the
stability set of first kind, CGA, CPSO and CFA are presented with discussion. An empirical optimization
model of biogas production has been constructed with accuracy of 90%. |
