Carbonic anhydrase is an important enzyme that can play a significant role in the processes of lowering carbon dioxide concentration in the atmosphere. The aim of the work was to investigate the extracellular carbonic anhydrase (CA) production by the bacteria Pseudomonas fragi. In the research, we focused on the evaluation of the phase of bacterial growth correlated with carbonic anhydrase production and on the evaluation of induction of CA production by calcium carbonate concentration in the nutrient medium. Presented data indicated that calcium carbonate can serve as the only carbon source for Pseudomonas fragi, inducing carbonic anhydrase secretion to culture broth. The enzyme was produced mainly in the adaptation growth phase reaching the maximal activity at the end of this phase or at the beginning of the growth phase. The maximal enzyme activity detected in all batches was at a similar level. The enzyme activity was constant but lower in the exponential phase growth. Therefore, the enzyme production is not growth-dependent, but it is correlated with bacteria adaptation to cultivation conditions.

The paper considers the production scheduling problem in a hybrid flow shop environment with sequence-dependent setup times and the objectives of minimizing both the makespan and the total tardiness. The multi-objective genetic algorithm is applied to solve this problem, which belongs to the non-deterministic polynomial-time (NP)-hard class. In the structure of the proposed algorithm, the initial population, neighborhood search structures and dispatching rules are studied to achieve more efficient solutions. The performance of the proposed algorithm compared to the efficient algorithm available in literature (known as NSGA-II) is expressed in terms of the data envelopment analysis method. The computational results confirm that the set of efficient solutions of the proposed algorithm is more efficient than the other algorithm.