A multi-objective approach based on genetic algorithm for multi-model line process planning considering difference in worker ability

This paper focuses on line process planning problem of multi-model (product type) assembly lines. The planning 1) assigns workers/operations to workstations for each model and 2) decides the production sequence of models. Since it is an NP-complete problem, a Genetic Algorithm (GA) based approach is adopted. Given the number of available workstations, a hybrid GA framework is proposed to find the Pareto optimization set instead of only one trade-off solution. Two parent selection strategies, by making use of Niched Pareto and weighted objective functions, are applied and compared. Moreover, a local heuristic strategy on worker allocation and operations assignment is proposed to avoid local optimal solutions and for obtaining better Pareto solution sets. Numerical analysis are conducted and the selection strategies using weighted objective functions is verified to perform better. Finally, the proposed heuristic strategy is confirmed to bring a further improvement of optimizing all the objectives.