Distributed assembly permutation flowshop scheduling problem based on IIGA

In this paper, an improved iterative greedy algorithm is proposed to solve the distributed assembly Permutation Flowshop Scheduling Problem. First, establish a mathematical model with the optimization goal of minimizing the total elapsed time and an improved iterative greedy algorithm is proposed, which uses a heuristic method combining CDS (campbell dudek smith) and NEH (nawaz-enscore-ham) to generate higher-quality initial solutions and improve population diversity; Secondly, design the destruction and reconstruction process for reconfigurable products and jobs, insert the removed sequence into the specified position, and use the local search strategy to obtain new solutions; Finally, the algorithm proposed in this paper is compared with other four intelligent algorithms through simulation experiments of different scales. The experimental results show that the improved iterative greedy algorithm has high efficiency and stability in solving distributed assembly replacement flow shop scheduling.