Different types of crude oils, including heavy sour crudes, are usually processed in oil refineries. They are suitably mixed in multipipeline crude oil blending systems (MCOBS) to get qualified feedstocks for the crude distillation units (CDUs) that separate them into various fractions or cuts. Current research on the scheduling of such refinery operations seeks to minimize the total operating cost while limiting the concentration of some impurities in the feedstock. However, an essential property like the feedstock composition usually approximated by the true boiling point (TBP) distribution curve is often ignored. In fact, one of the major goals of the blending process is to supply feedstocks to the CDUs that consistently produce the desi...
Gasoline blending is a critical process with a significant impact on the total revenues of oil refin...
The objective of this paper is the development and solution of nonlinear and mixed-integer (MIP) opt...
This work presents the mathematical formulation of a nonlinear programming (NLP) model which optimiz...
To increase profit margin, refiners usually upgrade low cost crude oils by mixing them with light cr...
Due to the impact of crude oil prices on refinery revenues, the petroleum industry has switched to p...
To increase profit margin, refiners usually upgrade low cost crude oils by mixing them with light cr...
Several types of crude oils arrive at inland oil refineries to be transformed into different interme...
This paper presents a novel MILP-based method that addresses the simultaneous optimization of the of...
Gasoline is one of the largest-volume products of the oil industry that yields 60%−70% of the total ...
In a previous paper, Alattas, Grossmann, and Palou-Rivera (2011) developed a single-period, nonlinea...
This work introduces a mixed-integer nonlinear programming (MINLP) formulation for the efficient pla...
This paper presents a solution algorithm and effective mathematical formulations for short-term sche...
The crude oil scheduling problem has been focus of many studies in the past, which is justified by i...
This thesis deals with the development of mathematical models and algorithms for optimizing refinery...
Process-oriented oil and chemical companies, like most industries, are becoming increasingly depende...
Gasoline blending is a critical process with a significant impact on the total revenues of oil refin...
The objective of this paper is the development and solution of nonlinear and mixed-integer (MIP) opt...
This work presents the mathematical formulation of a nonlinear programming (NLP) model which optimiz...
To increase profit margin, refiners usually upgrade low cost crude oils by mixing them with light cr...
Due to the impact of crude oil prices on refinery revenues, the petroleum industry has switched to p...
To increase profit margin, refiners usually upgrade low cost crude oils by mixing them with light cr...
Several types of crude oils arrive at inland oil refineries to be transformed into different interme...
This paper presents a novel MILP-based method that addresses the simultaneous optimization of the of...
Gasoline is one of the largest-volume products of the oil industry that yields 60%−70% of the total ...
In a previous paper, Alattas, Grossmann, and Palou-Rivera (2011) developed a single-period, nonlinea...
This work introduces a mixed-integer nonlinear programming (MINLP) formulation for the efficient pla...
This paper presents a solution algorithm and effective mathematical formulations for short-term sche...
The crude oil scheduling problem has been focus of many studies in the past, which is justified by i...
This thesis deals with the development of mathematical models and algorithms for optimizing refinery...
Process-oriented oil and chemical companies, like most industries, are becoming increasingly depende...
Gasoline blending is a critical process with a significant impact on the total revenues of oil refin...
The objective of this paper is the development and solution of nonlinear and mixed-integer (MIP) opt...
This work presents the mathematical formulation of a nonlinear programming (NLP) model which optimiz...