We consider an analogy between the plan optimization process and the genetic evolution process. We define crossover and mutation operations to make a new plan like as a process of the evolution of the life. We simulate evolution processes of plan using the above operation in order to solve the activity-location problem that is formulated as a minimization problem of a total cost of communications between rooms. As a result, we get an optimal clan in fourth generation. Comparing the permutational method, the proposed genetic algorithm based on an analogy between the plan optimization and the evolution process is effective.
