A differential evolution with reinforcement learning for multi-objective assembly line feeding problem

•A novel multi-objective assembly line feeding problem is investigated.•Optimizing objectives simultaneously without weights derived from prior knowledge.•Receiving warehouses, inventory strategies, and policy switching are considered.•An efficient and cost-saving algorithm is proposed, validated, and analysed.•Managerial insights are obtained for decision support in implementation.