Enhanced models for large scale supply chain tactical planning problems

供应链是关于协作，以顺利管理产品需求。随着产品（以及合作伙伴）数量的增加，供应链规划变得复杂。计划中的大部分困难来自需求、供应、时间等方面的不确定性。不确定参数越多，规划难度越大。以自然资源为基础的供应链，如森林/农产品供应链，就是这样一个供应链，在各个层面的不确定性都很高，产品数量巨大。为了管理这些不确定性，管理者要么选择高水平的冗余，也就是说，要么缓冲供应链上所有级别的库存，要么进行多重采购，等等。所有的选择都有优点和缺点。多种策略的可用性使得决策和供应链规划变得更加复杂。为了顺利地管理供应链，其中一个选择是限制产品的数量。然而，企业提供一系列的产品来迎合大量的客户。在这种情况下，为了保持供应链的精益，产品被设计成这样一种方式，即大多数最终产品共享许多共同的组件（原材料）。换句话说，一个组件可以用于许多不同的产品。有两个极端：为每个产品设计特定于产品的组件；并设计一个单一的通用组件，可以适用于每一个产品。两种极端都有优点和缺点，为了平衡与这两种极端相关的优点和缺点，最终产品被分成不同的类别，每个类别共享组件。例如，一个特定宽度的轧辊可以用来生产几种最终产品。品类数量的确定和品类产品的分类是一个非常复杂的问题。在数学术语中，这个问题被称为集合划分问题，在实践中称为分类问题。在供应链中，我们在不同的层次上遇到了许多分类类型的问题。例如，为有容量限制的多种产品选择供应商，为仓库分配零售商，为有先例限制的多种工作选择承包商，资源分配等。由于与容量、成本和随机性相关的非线性，解决这些问题并不容易。在以天然产品为基础的供应链中，高浪费和有限的替代供应（在最后一刻）是非常常见的。正确的分类计划是保持供应链顺畅和运营成本最低的唯一途径。在本研究中，我们的目标是对相关文献进行系统的综述，并通过提供新的工具来丰富现有的知识，以解决这些复杂的问题。我们将确定关键的战术水平规划问题，并开发基于数学建模的方法。根据问题的复杂性、问题的大小和使用情况，我们将开发和测试各种方法的组合。将通过出版物和讨论会传播最有效和最适当的办法。特别是，我们的主要目标是：1)开发和测试更适合这些情况下供应链的策略。2)发展数学规划解决方法，有效和高效地解决这种复杂的模型。3)开发/探索测试用例，对性能进行基准测试。这项研究的结果将是一套规划工具，可以帮助该行业改进规划，从而提高成本效益和竞争力。这项研究的其他成果包括培训了几名高素质的研究人员，并进一步推动了该领域的发展。产生的结果将通过出版物、会议报告分享。

Supply chain is all about collaboration for managing the product demand smoothly. The supply chain planning becomes complex as the number of products (and thus partners) grows. Most of the difficulty in planning arises from the uncertainties in demand, supply, time, etc. The more the number of uncertain parameters, the more difficult the planning is. Natural resources based supply chains such as forest/agro product supply chain are one of such supply chains where uncertainties at all levels are high with huge number of products. To manage these uncertainties, either managers opt for high level of redundancy, that is, either buffer stocks at all levels across the supply chain or do multiple sourcing, etc. All the options come with advantages and disadvantages. Availability of multiple strategies makes decision making and supply chain planning more complex. To manage the supply chain smoothly, one of the options is to limit the number of products. However, businesses offer a portfolio of products to cater a large pool of customers. In this situation, to keep the supply chain lean, products are designed in such a way that most of the final products share lot of common components (raw material). In other words, a component can be used in many different products. There are two extremes: Designing the product specific component for each product; and designing a single universal component that can fit in every product. Both extremes have advantages and disadvantages and to balance the advantages and disadvantages associated with the both extremes, final products are segregated into different categories and each category shares the component. For instance, a roll of a specific width can be used to produce several final products. Determination of number of category and classification of products in categories is a very complex problem. In mathematical terms, the problem is known as set partition problem and in practice called the assortment problem. In supply chains we encounter numerous assortment type problems at various levels. For instance, selecting suppliers for multiple products with capacity restrictions, assigning retailers to warehouses, selecting contractors for multiple jobs with precedent constraints, resource assignments, etc. Resolving these problems are not easy due to non-linearity associated with capacity, cost and randomness. High waste and limited alternative supply (at the last moment) are very common in natural products based supply chains. Proper assortment planning is the only way to keep the supply chain smooth and operating cost minimal. In this research, our goal is to do systematic review of the relevant literature and enrich the existing knowledge by contributing novel tools to solve such complex problems. We will identify key tactical level planning problems and develop mathematical modeling based approaches. Based on the problem complexity, problem size and usage we will develop and test combination of approaches. Most effective and suitable approaches will be disseminated through publications and seminars. In particular, our main objectives are: 1) Develop and test strategies which are more suitable for supply chains under these circumstances. 2) Develop mathematical programming solution approaches which are effective and efficient in solving such complex models. 3) To develop /explore test cases for bench-marking the performance. The outcome of this research will be a set of planning tools that can help the industry in improved planning and thus more cost effective and competitive. Other outcomes of the research include training of several highly qualified personnel for research and further advancement of the field. The generated results will be shared through publications, conference presentations.