MIXED INTEGER OPTIMIZATION IN THE CHEMICAL PROCESS INDUSTRY Experience, Potential and Future Perspectives

Proper organization, planning and design of production, storage locations, transportation and scheduling are vital to retain the competitive edge of companies in the global economy. Typical additional problems in the chemical industry suitable to optimization are process design, process synthesis and multi-component blended-flow problems leading to nonlinear or even mixed integer nonlinear models. Mixed integer optimization (MIP) determines optimal solutions of such complex problems; the development of new algorithms, software and hardware allow the solution of larger problems in acceptable times. This paper addresses two groups. The focus towards the first group (managers & senior executives) is to create some awareness regarding the potential benefits of MIP, to transmit a sense of what kind of problems can be tackled, and to increase the acceptance of MIP. The second group (a more technical audience with some background in mathematical optimization) might rather appreciate the state-of-the-art view on goodmodeling practice, algorithms and an outlook into global optimization. We present real-world MIP problems solved by BASF’s mathematical consultants: discrete blending, multi-stage production planning and distribution with several sites, products and periods, a site analysis of one of BASF’s bigger sites, and a process design problem. Finally, we focus on future perspectives and indicate sources of MIP support from academia, software providers and consulting firms.