Abstract: The rising production flexibility in response to personalized consumer demands highlights the importance of cost control and resource management.Consequently,the resource-constrained order acceptance and scheduling problem has become critical for C2M enterprises.A mixed-integer programming model was developed to determine the optimal order acceptance strategy,incorporating constraints on renewable and non-renewable resources and aiming to maximize profit.To solve the model,the Logic-based Benders Decomposition (LBBD) algorithm was employed,which decomposed the model into a master problem and subproblems.In view of the difficulty of solving the main problem,a branch and check strategy was introduced to ensure efficient search for feasible solutions.After getting a feasible solution,the subproblems were further solved to generate the cut,and two optimality cuts were proposed based on the combinational Benders cuts to speed up the solution.Numerical experiments demonstrated that the improved strategy significantly enhanced solving speed for small to medium-scale instances.However,traditional model and the LBBD strategy perform poorly under large-scale instances.In contrast,the improved strategy consistently achieves global optimality across all scales.Significantly,the consideration of renewable resources was crucial for evaluating the number of accepted orders.

Key words: customer-to-manufacturer, order acceptance and scheduling, logic-based Benders decomposition algorithm, branch and check strategy

摘要： 在消费需求日益个性化的环境下,企业生产的柔性化程度不断提高,这使得成本控制与资源管理变得更加重要。因此,资源限制下的订单接受与调度问题成为C2M企业亟待解决的问题。为了合理评估接受订单数量,综合考虑可再生资源与不可再生资源约束,并以最大化利润为目标函数,建立了混合整数规划模型。在模型的求解方面,采用基于逻辑的Benders分解(LBBD)算法将原模型分解为主问题和子问题。针对主问题求解困难的特点,引入分支检查策略确保高效的可行解搜索,获得可行解后,进一步求解子问题以生成切割。为加速求解,在组合型切割的基础上提出了两个最优切割。数值实验表明:中小规模算例下,改进方案求解速度明显提升;大规模算例下,传统模型和LBBD策略的求解质量大幅下降,但改进方案仍能求得全局最优解;考虑可再生资源对于评估订单接受数量至关重要。

关键词: 客户直通制造, 订单接受与调度, 基于逻辑的Benders分解算法, 分支检查策略