This invention provides a means to minimize the costs of technical and business processes. These processes are comprised of resources and tasks requiring resources. The optimization consists of the best assignment of resources to tasks to minimize the costs. In the resource assignment optimization method disclosed herein, Genetically Adapted Search Agents (GASA) are employed to improve a population of possible assignments, each represented by a single variable length chromosome, where the chromosome upon which the GASA operates is a direct encoding of possible resource to task assignments and order. To manage the enlarged search space, this method uses the GASA with substring crossover to evolve the population towards better solutions. The assignments generated by this method satisfy all constraints.