Computational Experience with Piecewise Linear Relaxations for Petroleum Refinery Planning

Abstract

Refinery planning optimization is a challenging problem as regards handling the nonconvex bilinearity, mainly due to pooling operations in processes such as crude oil distillation and product blending. This work investigated the performance of several representative piecewise linear (or piecewise affine) relaxation schemes (referred to as McCormick, bm, nf5, and nf6t) and de (which is a new approach proposed based on eigenvector decomposition) that mainly give rise to mixed-integer optimization programs to convexify a bilinear term using predetermined univariate partitioning for instances of uniform and non-uniform partition sizes. The computational results showed that applying these schemes improves the relaxation tightness compared to only applying convex and concave envelopes as estimators. Uniform partition sizes typically perform better in terms of relaxation solution quality and convergence behavior. It was also seen that there is a limit on the number of partitions that contribute to relaxation tightness, which does not necessarily correspond to a larger number of partitions, while a direct relationship between relaxation size and tightness does not always hold for non-uniform partition sizes.

Interconnectedness between Supply Chain Resilience, Industry 4.0, and Investment

“…The research highlights the potential of these I4.0 technologies to improve SC resilience and cybersecurity, but also notes the need for careful consideration of ethical and legal issues. The authors identify several factors that influence the impact of AI on workplace outcomes, including the level of employee involvement in AI implementation, the degree of task complexity, and the level of trust and transparency in AI decisionmaking processes [94][95][96][97].…”

Do the True Boiling-Point Distillation Yields of Crude Oil Blends Obey the Additive Blending Rule?

“…The complexity of refinery operations makes it difficult to formulate the suitable planning optimization models [9]. One of the challenges in the linear programming models is how to properly represent the operation of crude distillation units (CDUs) [8,10]. They are among the most important process units in the refinery because they separate the crude oil in fractions (naphtha, kerosene, diesel oil, atmospheric residue, vacuum…”

“…An inaccurate CDU operation representation will give inaccurate yields of the intermediate streams, and the entire downstream processing modelling will be erroneous. Thus, the overall economic performance evaluation of the refinery is directly influenced by the proper simulation of CDU operation [8,10]. Different models of CDU operation simulation have been reported in the literature [7,[11][12][13].…”