Enhancing the Decision Making Process for Paper Mill Schedulers, 1998 Finishing and Converting Conference Proceedings

In this paper, we discuss a new decision-support system for scheduling paper manufacturing and distribution. Scheduling production and distribution of paper is an extremely complex task requiring the consideration of numerous constraints and objectives. Problem complexity is compounded by process interactions wherein the scheduling of one stage of the production process may negatively impact downstream processes. In contrast to earlier approaches, the system considers multiple scheduling objectives and multiple stages of paper manufacturing and distribution simultaneously in a global multi-criteria optimization framework. It generates multiple scheduling alternatives by using several algorithms based on approaches such as linear/integer programming, network flow methods and heuristics. These alternatives reveal tradeoffs with respect to competing objectives, such as maximizing profitability, on-time delivery, product quality, and minimizing manufacturing disruptions. Each scheduling alternative is a complete enterprise schedule that includes sub-schedules for each stage of the manufacturing process and loading. The scheduler can work cooperatively with the system to explore alternatives and to improve solution quality. As the final decision maker, the scheduler can choose the best alternative for the enterprise. By functioning as an intelligent assistant, the system relieves the schedulers of mundane computational tasks and allows them to focus on the objectives of the enterprise and decision making. For generating multiple solutions and facilitating cooperation with the scheduler, the system is implemented using the agent based Asynchronous Team (A-Team) architecture in which multiple solution methods cooperate by evolving a shared population of solutions. The successful deployment of the system at several paper mills in North America has resulted in significant savings and improved customer satisfaction. These positive results arose from improved schedule quality and improvements in the business process that the decision-support approach has fostered.