During the last two decades, an increasing number of large pharmaceutical companies have decided to outsource part of their operations to reduce costs and mitigate their risk exposure. Contract Manufacturing Organizations (CMOs) utilize their facilities to manufacture products for multinational pharmaceutical companies on a contract basis. These organizations must define which contracts to accept to maximize their profit while considering their risk tolerance. This work presents an integrated tactical planning and medium-term scheduling framework for the optimal contract appraisal problem of Contract Manufacturing Organizations in the secondary pharmaceutical industry under demand uncertainty. An aggregated MILP-based planning model is proposed, along with a general precedence MILP model for the scheduling of multi-stage, multiproduct, batch industries. Production targets are defined in the planning decision level using a rolling horizon framework, while the scheduling model takes batch-sizing, sequencing and timing decisions in detail. A three-phase, scenario-based solution algorithm is introduced to model demand uncertainty considering Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) measures, while both systematic and unsystematic risk are considered. Results illustrate that the proposed modelling framework provides a systematic approach for the contract appraisal problem of Contract Manufacturing Organizations as it can select the optimal contract mixture depending on the corresponding risk tolerance.

在过去的二十年里，越来越多的大型制药公司决定将其部分业务外包，以降低成本并减轻风险。合同制造组织 (CMO) 在合同基础上利用其设施为跨国制药公司制造产品。这些组织必须在考虑风险承受能力的同时，定义接受哪些合同以实现利润最大化。这项工作为需求不确定下二级制药行业合同制造组织的最优合同评估问题提出了一个集成的战术规划和中期调度框架。提出了一种基于 MILP 的聚合计划模型，以及用于调度多阶段、多产品、批处理行业。生产目标是在计划决策级别使用滚动范围框架定义的，而调度模型则详细采用批量大小、排序和时间决策。引入了三阶段、基于情景的解决方案算法来模拟需求不确​​定性，考虑风险价值 (VaR) 和条件风险价值 (CVaR) 措施，同时考虑系统性和非系统性风险。结果表明，所提出的建模框架为合同制造组织的合同评估问题提供了一种系统的方法，因为它可以根据相应的风险承受能力选择最佳的合同组合。详细的排序和时序决策。引入了三阶段、基于情景的解决方案算法来模拟需求不确​​定性，考虑风险价值 (VaR) 和条件风险价值 (CVaR) 措施，同时考虑系统性和非系统性风险。结果表明，所提出的建模框架为合同制造组织的合同评估问题提供了一种系统的方法，因为它可以根据相应的风险承受能力选择最佳的合同组合。详细的排序和时序决策。引入了三阶段、基于情景的解决方案算法来模拟需求不确​​定性，考虑风险价值 (VaR) 和条件风险价值 (CVaR) 措施，同时考虑系统性和非系统性风险。结果表明，所提出的建模框架为合同制造组织的合同评估问题提供了一种系统的方法，因为它可以根据相应的风险承受能力选择最佳的合同组合。