An Iterated Greedy Algorithm Based on Accelerated Calculation for Distributed Flowshop Group Scheduling Problem with Blocking Constraints

Today’s industrial production models are becoming increasingly complex. Jobs of the same type are usually divided into groups for machining. Factories are often designed in a distributed structure, i.e., they are built in serval different locations. The distributed flowshop group scheduling problem with blocking constraints (DBFGSP) has not been well studied. We constructed a mixed-integer linear programming model, and an iterated greedy algorithm based on the accelerated calculation (IGACA) to reduce the time complexity. We use 810 instances to compare our proposed algorithm with four other excellent algorithms used to solve related problems. The experimental result shows that our proposed algorithm is advantageous in solving the DBFGSP.