Integer linear programming enables optimal decision making in supply chain management operations

Effective supply chain management is one of the key business processes of any manufacturing company. The need for a systematic decision making framework in supply chain applications is especially pronounced when available supply does not meet the demand and it becomes necessary to prioritize deliveries among customers and manufacturing among products. To address this challenge, the production planning task is formulated as an integer linear programming problem (ILP). This allows to optimally allocate the available raw materials in a considered time horizon according to a selected financial objective (such as net sales maximization) and under real-world constraints (e.g. manufacturing capacities of factories). The developed approach is demonstrated on two practical use cases: 1) verification whether an ad-hoc increase in components supply at a premium cost translates into an increased production output and is thus to commercial benefit; and 2) evaluation of commercial implications of prioritizing deliveries to selected customers. The proposed optimization algorithm is a key enabler of a systematic supply chain decision-making framework, enabling quick response to challenging supply situations thanks to combining optimization techniques with data-driven business paradigm.