0000000000114513
AUTHOR
G Vivó-truyols
A hybrid genetic algorithm with local search: I. Discrete variables: optimisation of complementary mobile phases
Abstract A hybrid genetic algorithm was developed for a combinatorial optimisation problem. The assayed hybridation modifies the reproduction pattern of the genetic algorithm through the application of a local search method, which enhances each individual in each generation. The method is applied to the optimisation of the mobile phase composition in liquid chromatography, using two or more mobile phases of complementary behaviour. Each of these phases concerns the optimal separation of certain compounds in the analysed mixture, while the others can remain overlapped. This optimisation approach may be useful in situations where full resolution with a single mobile phase is unfeasible. The o…
Complementary mobile-phase optimisation for resolution enhancement in high-performance liquid chromatography.
An optimisation methodology in high-performance liquid chromatography (HPLC) is presented for the selection of two or more mobile phases having an optimal complementary resolution. The complementary mobile phases (CMPs) are selected in such a way that each one resolves optimally only some compounds in the mixture, while the remainder, resolved by the other mobile phase(s), can overlap among them. The methodology is based on the computation of a peak purity measurement for each solute, using an asymmetrical peak model for peak simulation. Two global resolution criteria (product of elementary resolutions and worst elementary resolution) and two methods for solving the problem (a systematic ex…
A hybrid genetic algorithm with local search
Abstract A hybrid genetic algorithm with internal local search was developed for optimisations involving continuous variables. The reproduction probabilities were enhanced using the fitness values obtained when a local method was applied to each individual in the population. These estimations are more realistic, since consider not the apparent but the hidden, latent quality of each individual. The information gathered in the local search was also used to build an auxiliary population recording the successfully enhanced individuals, which allowed to detect the convergence and self-adapt the search limits. The size of this auxiliary population was kept constant by a cluster analysis strategy.…