Optimization, Genetic Algorithm, Operations Research, Scheduling, Data Science.
solutions each time, applying crossover and mutation, and evaluating the fitness of the new generation. Problem and Approach Initially, the genetic algorithm rapidly converged to a local optimum where all feasible solutions had similar makespans. This indicated a lack of diversity in the population