An Iterated Local Search Algorithm for the Lot-Streaming Flow Shop Scheduling Problem

The lot-streaming flow shop scheduling problem plays an important role in modern industry. This paper addresses this problem with the objective of minimizing the total weighted earliness and tardiness penalties and then proposes a simple but effective iterated local search (ILS) algorithm. In the proposed ILS algorithm, an adapted Nawaz–Enscore–Ham (NEH) heuristic is used to generate an initial solution. A local search procedure based on the insertion neighborhood is employed to perform local exploitation. A simulated-annealing-typed acceptance criterion is utilized to determine the start point for next iteration. Extensive experiments are conducted to compare the proposed ILS algorithm with some existing algorithms. The computational results and comparisons demonstrate the effectiveness of the proposed ILS algorithm.