Novel Modeling and Analytical Approaches for Primary Pharmaceutical Manufacturing Scheduling and Related Problems

制药生产调度及相关问题的新的建模和分析方法. Sarin和Hanif D. SheraliThis赠款为开发优化模型和算法提供资金，用于分析药品供应链的主要制造操作阶段，该阶段负责生产活性药物成分。所设计的方法将确定药品到主要生产设施的各个加工区的最佳分配和排序，以便以最低的生产成本（包括所需的设置和为实现快速周转而产生的库存的贡献）满足客户要求，给定一组具有指定容量的设备以及每种产品的产品组合和需求率。将开发一种基于分解的方法，用于确定（接近）最佳的排序、分配和排序决策。还将研究实践中出现的某些重要特殊情况。将在勃林格殷格翰化工厂（位于弗吉尼亚州彼得堡，致力于为制药行业生产活性药物成分和中间体）遇到的实际问题实例中测试开发的模型和解决方法。如果成功，本研究的结果将通过减少实践中的周期时间延迟来提高对市场需求的响应能力，同时降低制造成本。研究的模型包括作为子结构的高多重性不对称旅行商问题和经典的车间作业调度问题。多面体分析的基础上提出的研究工作也将有助于提高这些问题的独立解决方案，这是重要的，在自己的权利。此外，拟议的研究将有助于为分析其他批量生产设施（如半导体制造）提供见解和计算工具。

AbstractNovel Modeling and Analytical Approaches for Primary Pharmaceutical Manufacturing Scheduling and Related ProblemsPIs: Subhash C. Sarin and Hanif D. SheraliThis grant provides funding for developing optimization models and algorithms for analyzing the primary manufacturing operational stage of the pharmaceutical supply chain, which is responsible for the production of active pharmaceutical ingredients. The designed approach will determine optimal assignment and sequencing of pharmaceutical products to various processing bays of a primary manufacturing facility in order to meet customer requirements at minimal production costs (which include contributions from both the setups required and inventory incurred to achieve a quick turn-around), given a set of equipments with specified capacities as well as a product-mix and demand rate for each product. A decomposition-based methodology will be developed for determining (near-) optimal batching, assignment, and sequencing decisions. Certain important special cases that arise in practice will also be studied. The models and solution methodologies developed will be tested on real-life problem instances encountered by the Boehringer Ingelheim Chemical plant, located in Petersburg, Virginia, which is devoted to the production of active pharmaceutical ingredients and intermediaries for the pharmaceutical industry.If successful, the results of this research will lead to increasing the responsiveness to market demand by reducing cycle time delays in practice, while curtailing manufacturing costs. The models to be investigated include as substructures the high multiplicity asymmetric travelling salesman problem and the classic job shop scheduling problem. The polyhedral analysis based on the proposed research effort will also serve to enhance the independent solution of these problems, which are important in their own right. In addition, the proposed research will contribute toward providing insights and computational tools for analyzing other batch production facilities, such as in semiconductor manufacturing.