Submit  |   Chinese  |
Engineering
 Home  |  Online Now  |  Current Issue  |  Focus  |  Archive  |  For Authors  |  Journal Information Open Access
 Submit  |   Chinese  |
 Engineering    2017, Vol. 3 Issue (2) : 188 -201     https://doi.org/10.1016/J.ENG.2017.02.005
 Research |
Global Optimization of Nonlinear Blend-Scheduling Problems
Pedro A. Castillo Castillo1,Pedro M. Castro2,Vladimir Mahalec1()
1. Department of Chemical Engineering, McMaster University, Hamilton, ON L8S 4L8, Canada
2. Center for Mathematics, Fundamental Applications and Operations Research, Faculty of Sciences, University of Lisbon, Lisbon 1749-016, Portugal
Abstract
 Abstract  The scheduling of gasoline-blending operations is an important problem in the oil refining industry. This problem not only exhibits the combinatorial nature that is intrinsic to scheduling problems, but also non-convex nonlinear behavior, due to the blending of various materials with different quality properties. In this work, a global optimization algorithm is proposed to solve a previously published continuous-time mixed-integer nonlinear scheduling model for gasoline blending. The model includes blend recipe optimization, the distribution problem, and several important operational features and constraints. The algorithm employs piecewise McCormick relaxation (PMCR) and normalized multiparametric disaggregation technique (NMDT) to compute estimates of the global optimum. These techniques partition the domain of one of the variables in a bilinear term and generate convex relaxations for each partition. By increasing the number of partitions and reducing the domain of the variables, the algorithm is able to refine the estimates of the global solution. The algorithm is compared to two commercial global solvers and two heuristic methods by solving four examples from the literature. Results show that the proposed global optimization algorithm performs on par with commercial solvers but is not as fast as heuristic approaches. Fund: Corresponding Authors: Vladimir Mahalec Just Accepted Date: 28 March 2017   Online First Date: 21 April 2017    Issue Date: 27 April 2017