Differential Evolution Flexible Integrated Assembly Production Distribution Scheduling (DE-FIAPDS)

This study addresses the gap in research on distributed integrated scheduling for complex products by presenting a tree-structured framework enhanced with Differential Evolutionary Flexible Integrated Assembly Production Distribution Scheduling (DE-FIAPDS). The algorithm’s effectiveness is demonstrated by validating standard benchmark problems and custom-generated test cases. Using Taguchi’s method and comparative analysis, we developed GA and DE heuristic evolutionary algorithms for the scheduling problem. Over the course of 30 independent replications, applied to 100 randomly generated instances, the DE-FIAPDS algorithm was observed to produce an average final-generation makespan. We calculate the time complexity of the basic DE by combining these additional steps with the basic DE time complexity, such as forward conversion, backward conversion and local search, which can be expressed as O(Gmax·Npop·(d+noplognop)), where Gmax is the maximum number of generations, Npop is the number of individuals in the given population, d is the dimension of the problem, and nop is the the number of operations in FIAPDS. The proposed DE-FIAPDS gives the same results as GA-FIAPDS, although in some instances they differ by a huge difference in makespan. On the other hand, its computing time was 100 times quicker.