Hybrid bidirectional ant colony optimization (hybrid BACO): An algorithm for disassembly sequence planning

In traditional disassembly sequence planning (DSP), a disassembly sequence is planned based on the description of the product design and personal experience. Research on disassembly sequence planning needs to take into account the relationship between the parts and related factors, such as changes in orientation and tools, so as to optimize the order of the disassembly sequence. Among the numerous feasible disassembly sequences, it is important for researchers to find the most economical DSP, which becomes more difficult as the number of parts increases. In this study, a hybrid bidirectional ant colony optimization (Hybrid BACO) algorithm is proposed and compared with four related algorithms. Simulated cases show that the hybrid BACO algorithm provides a better solution than other ant algorithms. The five ant algorithms are also compared from the viewpoint of a reverse assembly sequence, and the results again show that the Hybrid BACO algorithm provides the best solution quality.