A unified homogeneous quadratically constrained quadratic program is used to solve the optimization problems.
The CVX package [18] for specifying and solving convex programs was used to solve (10) to (12).
Recently, this kind of programming was used to solve problems arising in fields such as bioinformatics, computational biology, molecular biology, wastewater treatment, drug discovery, and food processing.
Since the resulting model was underdetermined, linear programming was used to solve for optimal fluxes.
Linear programming was used to solve the optimization problem where we examined three objective functions: maximum biomass production (a measure of cell growth), maximum uptake of 1,2,4-TCB (an indication of the rate of biodegradation), and minimum utilization of 1,2,4-TCB.
The point estimation method and second-order conic programming are used to solve the two-level model to guarantee a globally optimal solution and improved computational efficiency.
When mathematical programming is used to solve a problem and the number of decision variables is too high or constraint conditions are too complex, computation time is long, resulting in low efficiency, and can easily become trapped in partial optimum solution.
We solved this problem utilizing the same Matlab program as was used to solve the above example.
A finite element-computer simulation program – FEMLAB was used to solve the electromagnetic and Navier Stoke equations for developing a model to study the effect of dielectric properties of a model fruit and its surrounding medium.
The CNS v. 1.0 program suite was used to solve the structure by molecular replacement.
