This study proposes a logic-based modeling approach within a mixed-integer superstructure optimization framework on the topological optimization problem of determining the optimal configuration of a petroleum refinery. We are interested in further investigating and advancing the existing optimization approaches and strategies of employing logical constraints to conceptual process synthesis problems within the frameworks of the conventional Mixed-Integer Linear Program (MILP) and the alternative Generalized Disjunctive Program (GDP). In particular, we intend to address the following issues: (a) how the formulation of design specifications in a synthesis problem can be accomplished using logical constraints in a mixed-logical-and-integer optimization model to enrich the problem representation by way of incorporating past design experience, engineering knowledge and heuristics and (b) how structural specifications on the interconnectivity relationships by space (states) and by function (tasks) should be properly formulated using logical constraints within a mixed-integer optimization model. The proposed modeling technique is illustrated on a case study involving the alternative processing routes of naphtha in a refinery.
Cheng Seong Khor, Xiao Qi Yeoh and Nilay Shah, 2011. Optimal Design of Petroleum Refinery Topology using a Discrete Optimization Approach with Logical Constraints. Journal of Applied Sciences, 11: 3571-3578.