Solving robotic distributed flowshop problem using an improved iterated greedy algorithm

Abstract

In this study, we propose an improved iterated greedy algorithm for solving the distributed permutation flowshop problem, where there is a single robot in each factory and the makespan needs to be minimized. In the problem considered, the robot is used to transfer each job from the predecessor machine to the successor machine. A blocking constraint between machines is considered, thus jobs should remain on the completed machine while waiting for the robot. The loading and unloading times are considered and different for all of the jobs conducted by the robot, and the deteriorating time is also considered. In the proposed algorithm, first, four types of neighborhood structures are developed. Then, the simulated annealing algorithm is embedded in the proposed algorithm to enhance the exploration abilities. Furthermore, a problem-specific destruction and construction strategies are investigated. Finally, several realistic instances were generated to test the proposed algorithm, and its competitive performance was verified based on detailed experimental comparisons.