This repository includes the files of the manuscript Systematic Solving Study for Optimization of the Multiperiod Blending Problem: A Multiple Mathematical Approach Solution Guide.
The Multiperiod Blending Problem is highly used in different industry applications. This problem is a non-convex MINLP which has been solved for instances with a limited number of variables; hence, determining the best approach and the best solution algorithm is desirable. In this paper, six different approaches for the multiperiod blending problem are tested in terms of global optimality and computational time using a new set of problem instances. The solution methods discussed are the standard MINLP formulation, the relaxation created using McCormick envelopes, a Radix-Based Discretization, a generalized disjunctive programming (GDP) formulation, a Redundant Constraint GDP formulation, and a Two-Stage MILP-MINLP Decomposition. Results obtained show that the best approaches to solve are the standard MINLP and the Two-Stage MILP-MINLP Decomposition in terms of optimality and computational time, respectively.