Hybrid Multi-objective Optimization Method for Solving Simultaneously the line Balancing, Equipment and Buffer Sizing Problems for Hybrid Assembly Systems

In today's dynamic and uncertain markets, companies are required to regularly renew their product and process platforms through new production technologies and factory infrastructure. This results in shortening products', processes' and factories life cycle, engendering in return an increase of the complexity of assembly planning tasks, which are seen as increasingly uncertain and complex to control. This article presents a hybrid multi-objective optimization algorithm aiming at solving simultaneously the line balancing, equipment selection and buffer sizing problem under consideration of capacity and cost-oriented objectives. The proposed algorithm is compared to two classical evolutionary algorithms, the NSGA2 and SPEA2.