In this paper, a systematic framework for synthesis and design of processing networks under uncertaintyis presented. Through the framework, an enterprise-wide optimization problem is formulated and solvedunder uncertain conditions, to identify the network (composed of raw materials, process technologies andproduct portfolio) which is feasible and have optimal performances over the entire uncertainty domain.Through the integration of different methods, tools, algorithms and databases, the framework guidesthe user in dealing with the mathematical complexity of the problems, allowing efficient formulationand solution of large and complex enterprise-wide optimization problem. Tools for the analysis of theuncertainty, of its consequences on the decision-making process and for the identification of strategiesto mitigate its impact on network performances are integrated in the framework. A decomposition-based approach is employed to deal with the added complexity of the optimization under uncertainty. Anetwork benchmarking problem is proposed as a benchmark for further development of methods, toolsand solution approaches. To highlight the features of the framework, a large industrial case study dealingwith soybean processing is formulated and solved.
- Enterprise-wide optimization
- Integrated business and engineering
- Mixed-integer non-linear program (MINLP)
- Vegetable oil
- Process synthesis
- Product portfolio management