Abstract: Remanufacturing is an effective way to realize the reutilization of resources. Disassembly plays a key role in remanufacturing since it allows for the selective separation of desired parts from the end-of-life (EOL) products. Disassembly line is the best choiceto deal with EOL products on a large scale, so it is essential that it be designed and balanced to work efficiently. However, in the disassembly process, some parts may interact with each other and their disassembly times will be incremented by additional operations, and this affects the balance of disassembly line. In order to solve the disassembly interference among parts, in this research a sequence-dependent disassembly line balancing problem is presented with two objectives including minimization of the disassembly cost and environmental hazards. Then, a Pareto artificial bee colony algorithm is proposed for addressing this multi-objective optimization problem. A mixed strategy is designed to build an initial population with high quality and diversity, and some improvements are made in local exploitation and global exploration to accelerate the search speed. Finally, aset of benchmark instances is used to test the performance of the proposed algorithm. Computational results evidently indicate the superior efficiency of the proposed algorithm.In addition, a case study is presented to illustrate that balancing the tasks among workstations can effectively avoid the tasks with more time increments being disassembled on priority.

Key words: disassembly line balancing problem, sequence-dependent, artificial bee colony, Pareto