Integrated Scheduling Algorithm For Complex Products Based On The Dynamic Subtree Operation Set Inverse Coding

Abstract For the previous integrated scheduling algorithms for complex products, the migration time of operations between machines is ignored or just included in the processing time of its adjacent operations, which leads to inaccurate scheduling results and is difficult to meet the needs of the actual production scheduling environment. In this paper, based on the framework of a genetic algorithm, an integrated scheduling algorithm for complex products based on the dynamic subtree operation set inverse coding. Firstly, an inverse coding method based on the dynamic subtree operation set is proposed, which can ensure the legitimacy of the initial individuals and enhance the quality of the initial population. Secondly, based on the crossover vector, a single-point crossover method and a multi-point crossover method are proposed, both of which can ensure that the priority constraints among the same machine operation in the generated individuals will not be destroyed. Then, a mutation method based on the mutant row vector and mutant column vector is proposed to ensure the feasibility and diversity of the offspring individuals. Finally, a pre-decoding method based on device idle events driven and a conversion strategy of positive sequence schemes based on the completion time flipping are shown. The performance of the proposed algorithm is verified by several groups of comparative experiments.