In recent years, it is required to reduce the amount of waste since there is a growing interest in environmental issues. Hence, it is important to reuse and recycle the end-of-life products effectively. In the reusing and recycling process of products, a lot of components should be disassembled and inspected to get reusable parts from the products. Thus, it is necessary to carry out disassembly processes efficiently. However, it is difficult to find an optimal disassembly process since the complexity of the disassembly sequence increases with the number of parts of the products. Some studies have proposed scheduling methods using evolutionary algorithms to find a suitable disassembly schedule for a single product. However, these algorithms are considered neither the disassembly processes of multiple products nor the post processes of the disassembly processes, such as cleaning and inspecting, for reusing and recycling the parts disassembled from the products. In this paper, we propose a method using a genetic algorithm to find an optimal disassembly schedule considering both the disassembly processes of multiple products and the post processes for reusing and recycling the disassembled parts. A prototype of scheduling system is developed in order to verify the effectiveness of the proposed method. We carry out a large number of computational experiments though the developed scheduling system. The experimental results demonstrate that the new method is superior to the previous method from the viewpoint of the minimization of the whole disassembly and post-processing times.