On Different Algorithms for InterCriteria Relations Calculation

Contemporary InterCriteria analysis (ICrA) approach for searching of existing or unknown correlations between multiple objects against multiple criteria is applied here. Altogether five different algorithms for InterCriteria relations calculation have been examined to render the influence of the genetic algorithm parameters on the algorithm performance. Two cases, i.e. the model parameter identification of E. coli and S. cerevisiae fed-batch fermentation processes, are considered. In this investigation \(\mu \)-biased, Balanced, \(\nu \)-biased, Unbiased, as well as the newly elaborated and proposed here Weighted algorithm have been consequently applied and thoroughly examined. The obtained results for considered here two Case studies have been compared showing that the most reliable algorithm is the \(\mu \)-biased one.