Successive Linear Programming at Exxon

Successive Linear Programming (SLP) has been used extensively in the refining and petrochemical industries for over 20 years. This paper concentrates on some recent work at Exxon to unify the treatment of nonlinear terms in “mostly linear” models. We first discuss the source of nonlinearities in refining and petrochemical problems and propose a multiplicative formulation for the linearized subproblems to be solved by SLP. We then describe a SLP algorithm which is shown to be related to the concept of trust regions. Finally, we present an example formulation and computational results for a series of large industrial applications.