Uncertainty-Aware Planning and Scheduling in the Process Industries

由于全球不断扩大的生产和客户基础，工艺计划和调度问题变得越来越复杂。在不确定的情况下，决策者不断面临着优化生产计划和降低成本的挑战。不确定性可归因于各种因素，包括不稳定的客户需求、工艺性能的变化、生产工厂地点周围的社会经济波动等。另一个复杂的问题是必须作出和执行决定的时间尺度。不能有效地考虑这些问题可能会导致成本增加、客户不满、失去竞争优势，最终导致制造基地关闭。该项目旨在开发计划和调度工具，以便在不确定情况下进行最佳决策，同时考虑到多个时间尺度。每个工艺计划和调度问题都是独一无二的，因此一个建模和模型求解工具不能解决每个问题的特殊性。将不确定性归类为特定类别的框架是提供尖端最优解决方案的关键。因此，问题将具有许多不确定性，这些不确定性将根据我们提议的框架进行分类，然后针对每一分类调用适当的解决方案方法。还将开发一种混合的不确定性建模和优化工具，该工具利用各种不确定性解决方案技术的协同作用。在本项目中开发的新型计划和调度工具将在来自能源系统、农用化学品、制药、消费品、石油天然气和工业气体等多个行业的流程行业的真实案例研究中进行测试。将获得基于个性化不确定性的最优计划和调度解决方案。

Process planning and scheduling problems are becoming increasingly complex due to the expanding production and customer base around the globe. A decision maker is continuously faced with the challenge to optimise the production plans and reduce costs under uncertainty. The uncertainty can be attributed to factors including volatile customer demands, variations in the process performance, fluctuations in socio-economics around the locations of the production plants, etc. Another complicating issue is the time-scale at which the decisions have to be taken and implemented. Not being able to effectively take these issues into account can lead to increased costs, customer dissatisfaction, loss of competitive edge and eventually shutting down of the manufacturing bases. This project aims to develop planning and scheduling tools for optimal decision-making under uncertainty while taking into account the multiple time-scales. Each process planning and scheduling problem is unique and hence one modelling and model solution tool cannot address the peculiarities of each problem. A framework where uncertainties are classified into specific categories is the key to providing cutting-edge optimal solutions. So, a problem will have a number of uncertainties which will be classified based upon our proposed framework and then for each classification the appropriate solution methodology will be invoked. A hybrid uncertainty modelling and optimisation tool that exploits the synergies of the solution techniques for various classes of uncertainty will also be developed. The novel planning and scheduling tools developed in this project will be tested on real-life case studies from process industries from a wide variety of sectors including energy systems, agrochemicals, pharmaceuticals, consumer goods, oil & gas, and industrial gases. Optimal planning and scheduling solutions based upon personalised uncertainty will be obtained.