Abstract Competitors stand out through commitment to providing excellent customer service. Many organizations strive to promote their order promising system to generate more reliable quotes with quantity and due date constraints. This paper develops a Capable-to-Promise (CTP) based Order Acceptance Model (OAM) for a Hybrid Production Strategy (HPS) based on the positioning of the Customer Order Decoupling Points. The proposed model allocates the uncommitted availability and planned production receipts to current and anticipation of future needs. A Mixed-Integer Linear Programming (MILP) is developed to determine the optimal order quantities based on the resource availability. The proposed model efficiently mitigates the risk of not being reliable in the commitments due to discrepancies between the real and unused quantities. The CTP based OAM is compatible with a HPS with both make-to-order (MTO) and make-to-stock (MTS). The presented model encompasses four steps. First, demands for MTO products are collected in batches on daily basis and a forecasting model is applied to predict orders for MTS products. Secondly, the quantity-based Revenue Management approach is used to prioritize orders. Afterwards, the optimization model assesses the availability of resources in order to produce collected orders. The final step is to accept valuable orders based on the resource availability. In order to illustrate the applications of the modeling approach, two case studies are provided.

中文翻译：

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一种用于混合生产策略的高级订单接受模型

摘要 竞争对手通过致力于提供卓越的客户服务而脱颖而出。许多组织努力推广他们的订单承诺系统，以生成具有数量和截止日期限制的更可靠的报价。本文基于客户订单解耦点的定位，为混合生产策略 (HPS) 开发了一种基于承诺能力 (CTP) 的订单接受模型 (OAM)。提议的模型将未承诺的可用性和计划的生产收货分配给当前和未来需求的预期。开发了混合整数线性规划 (MILP) 以根据资源可用性确定最佳订单数量。由于实际数量和未使用数量之间存在差异，所提出的模型有效地降低了承诺不可靠的风险。基于 CTP 的 OAM 与具有按订单生产 (MTO) 和按库存生产 (MTS) 的 HPS 兼容。提出的模型包括四个步骤。首先，每天分批收集MTO产品的需求，并应用预测模型来预测MTS产品的订单。其次，基于数量的收入管理方法用于确定订单的优先级。之后，优化模型会评估资源的可用性以生成收集的订单。最后一步是根据资源可用性接受有价值的订单。为了说明建模方法的应用，提供了两个案例研究。每天分批收集MTO产品的需求，并应用预测模型预测MTS产品的订单。其次，基于数量的收入管理方法用于确定订单的优先级。之后，优化模型会评估资源的可用性以生成收集的订单。最后一步是根据资源可用性接受有价值的订单。为了说明建模方法的应用，提供了两个案例研究。每天分批收集MTO产品的需求，并应用预测模型预测MTS产品的订单。其次，基于数量的收入管理方法用于确定订单的优先级。之后，优化模型会评估资源的可用性以生成收集的订单。最后一步是根据资源可用性接受有价值的订单。为了说明建模方法的应用，提供了两个案例研究。