<p>Smart Card Data (SCD) is a valuable source of mobility datasets in public transit systems. While SCD commonly includes the time and location of passengers’ trips, it misses some important trip attributes, such as trip purpose types. Enriching SCD with the trip purpose attribute would extend the design and planning applications of this source of mobility data in public transit systems. In this study, an evolutionary approach, based on concepts of the genetic algorithm, is developed to solve the enrichment problem. The developed approach uses time (start time and duration of the activity, which happens between two subsequent trips) and location (available land use) of the trip destination to infer the trip purpose types. The relation between the time and location of the trips is learned from the Household Travel Survey (HTS). Firstly, the problem is defined and encoded in the genes and chromosomes. Secondly, the objective function is defined and formulated. Thirdly, the selection, cross over, and mutation operators repeatedly evolve each generation of solutions to generate better solutions until the breaking conditions are met. The case study is SCD data from southeast Queensland, Australia. Ultimately, two recent methods in the existing literature are reproduced, and their outcomes are compared with the proposed approach, which shows the high competitiveness between all three methods.</p>