An Effective Fruit Fly Optimization for the Distributed Assembly Flowshop Scheduling Problem

The distributed assembly flowshop scheduling problem has important applications in modern industries. For solving the problem with the objective of minimizing total flowtime, this paper proposes an effective fruit fly optimization (FFO) algorithm with a number of parallel swarms, each of which has its own osphresis foraging and vision foraging stages. The swarms are initialized by a LPT -based heuristic and find food sources using a hybrid operator which is a combination of the product-based and part-based insertion operators. A specific relinking procedure is presented to improve the cooperative search capability. To evaluate the proposed algorithm, we conduct a comprehensive set of computational and statistical experiments based on 910 benchmark instances. The results show that the proposed FFO algorithm performs significantly better than the existing methods in comparison.