This work aims to reduce the global resource consumption in an industrial evaporation network by better tasks management and coordination. The network works in continuous, processing some products in several evaporation plants, so optimal load allocation and product-plant assignment problems appear. The plants have different features (capacity, equipment, etc.) and their performance is affected by fouling inside the heat exchangers and external factors. Hereby, the optimizer has to decide when maintenance operations have to be triggered. Therefore, a mixed production/maintenance scheduling problem arises. The plant behavior is approximated by surrogate linear models obtained experimentally, allowing thus the use of mixed-integer linear optimization routines to obtain solutions in acceptable time. Furthermore, uncertainty in the weather forecast and in the production plan is also considered via a two-stage stochastic programming approach. Finally, a trade-off analysis between other objectives of interest is given to support the decision maker.

这项工作旨在通过更好的任务管理和协调来减少工业蒸发网络中的全球资源消耗。该网络连续运行，在多个蒸发工厂中处理一些产品，因此出现了最佳的负荷分配和产品工厂分配问题。这些设备具有不同的功能（容量，设备等），其性能会受到热交换器内部结垢和外部因素的影响。因此，优化器必须决定何时必须触发维护操作。因此，产生了混合的生产/维护计划问题。通过实验获得的替代线性模型可以近似工厂的行为，从而允许使用混合整数线性优化例程来在可接受的时间内获得解决方案。此外，天气预报和生产计划中的不确定性也通过两阶段随机规划方法来考虑。最后，在其他感兴趣的目标之间进行权衡分析，以支持决策者。