Parallel Disassembly Sequence Planning for Complex Products Based on Genetic Algorithm

In order to solve the parallel disassembly sequence planning（PDSP） problem efficiently, a method based on genetic algorithm was developed. According to the uncertain characteristics of disassembly sequence length and the number of parts removed at each step for the PDSP, a chromosome coding method for parallel sequence was presented to express the disassembly sequence and disassembly steps simultaneously. The disassembly hybrid graph（DHG） was constructed to describe the mating contact and disassembly priority relationships among constituting components of the product. From the DHG, the disassembly constraint matrix and adjacent matrix can be deduced so that the chromosome population with a feasibility constraint was generated randomly in order to reduce the search space. The chromosome fitness function combines the total disassembly time and the penalty factor for unfeasible disassembly sequences. Based on the fitness function, the crossover and mutation operation were performed to get the optimum sequence. Finally, an example illustrates the proposed method.