This paper deals with two scheduling problems occurring in the logistic CIM system and proposes methods for solving them by use of evolutionary computation. The first problem is the automated warehouse stock assignment problem and the second one is the automated flow rack stock assignment problem. Not only a well-known genetic algorithm but also two other evolutionary computation methods, an evolution program and evolutionary programming, are applied to the first problem in suit with problem formulation. It is seen that the evolution program brings a better convergence to this problem than other two. As this problem has plural criterion, the object function becomes multi-purpose scalar function by adding each criterion function with its proper weight. A weight tuning method is presented by use of the evolution program as well for a desired environment. The genetic algorithm is applied to the second problem. Experiments are performed by use of real problem data and its results are superior to the conventional ones Two experiments prove that evolutionary computation results take over conventional ones.