The quantity of waste electrical and electronic equipment (WEEE) is very large. WEEE not only occupies resources, but also easily pollutes the environment. The disassembly line is the most efficient way to address large-scale WEEE. How to improve disassembly profit and reduce energy consumption has become a significant and challenging research topic. However, the existing literature only considers the completely normal disassembly mode, ignoring the uncertainties such as corrosion and deformation of parts, and the evaluation system of the disassembly line cannot take into account both economic benefits and environmental impacts. Therefore, this paper introduces the destructive disassembly mode into the disassembly line and proposes a partial destructive disassembly line balancing model. The model aims to comprehensively optimize the number of stations, smoothness index, energy consumption, and disassembly profit. To obtain high-quality disassembly schemes, an improved genetic algorithm based on task precedence relationship is developed. Finally, the proposed model and method are applied to an engineering example of a television disassembly line. The performance of the proposed method is verified by comparing it with ant colony optimization, particle swarm optimization, artificial bee colony, and simulated annealing. The analysis of the disassembly schemes shows that the partial destructive mode can improve the disassembly profit and reduce energy consumption.