A Multi-Objective Memetic Algorithm for a Fuzzy Parallel Blocking Flow Shop Scheduling Problem of Panel Block Assembly in Shipbuilding

Scheduling plays an important role in improving the efficiency of panel block assembly. Because of the characteristics of the assembly lines and the imprecise and vague temporal parameters in real-world production, the scheduling of panel block assembly on parallel lines is formulated as a fuzzy parallel blocking flow shop scheduling problem with fuzzy processing time and fuzzy due date to minimize the fuzzy makespan and maximize the average agreement index. To solve this combinational optimization problem, a multi-objective memetic algorithm (MOMA) is proposed. In the MOMA, two novel heuristics are designed to generate several promising initial solutions, and a local search method is embedded to improve the exploitation capability. The performance of the MOMA is tested on the production instances of panel block assembly in shipbuilding. Computational comparisons of the MOMA with two other well-known multi-objective evolutionary algorithms demonstrate its feasibility and effectiveness in generating optimal solutions to the bi-criterion fuzzy scheduling problem of panel block assembly.