Order picking operation is one of the major sources of operating costs of a distribution center. The proper assignment of storages to stocks prior to their picking is critical to reduce such costs. Appropriate storage assignments can also shorten storing time, improve storage utilization, and facilitate inventory management. The storage assignment problem can be modeled as a quadratic assignment problem, which appertains to an NP-Complete problem, and hence creates difficulties in solving large scale problems. This study develops a genetic algorithm to solve the problem with three objectives: minimizing the routing length of storing stocks, maximizing the future chance of adjacent stocks to be picked together, and minimizing the storage distance to the access point for popular stocks. This study devises a genetic algorithm to find feasible solutions and uses a method to determine the final storage assignment from a set of Pareto solutions. Performance of the proposed approach is evaluated via a computer simulation based on historical orders of the case-study distribution center.