Decreasing product life cycles and reduced product development times have led to a need for new strategies for coping with the rapid rate of product family design changes. In this paper, assembly system reconfiguration planning (ASRP) is introduced as a method for cost effectively designing several generations of assembly systems in order to produce a product family that gradually evolves over time. In the ASRP approach, the possible assembly systems for each generation are first considered and then the sequence of assembly system configurations that minimize the life cycle cost of the process are selected. A nonlinear integer optimization formulation is developed for finding the cost minimizing assembly system reconfiguration plan using the ASRP approach. Dynamic programming and genetic algorithm are used to solve the optimization problem. Simulation results indicate that the ASRP approach leads to the minimum life cycle costs of the assembly system, and the relative cost of reconfiguration and production have an impact on the assembly system reconfiguration plan selected. Comparison of the results of the dynamic program and genetic algorithm indicate that the dynamic program is more computationally efficient for small problems and genetic algorithm is preferred for larger problems.