Discrete time reactive scheduling of gasoline blending and product delivery in presence of demand and component uncertainties using graphical genetic algorithm. (5th December 2020)

• Record Type: Journal Article
• Authors: Panda, Debashish; Bayu, Feleke; Ramteke, Manojkumar
• Is Part Of: Computers & chemical engineering. Volume 143(2020)
• Publication Date: 2020-12-05
• Subjects: Reactive scheduling -- Gasoline blending -- Component property uncertainty -- Demand increase -- Multi-objective optimization; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2020.107100
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: Reactive scheduling of gasoline blending and product delivery is solved. Uncertainties of component quality, demand increase and both are handled. Both the single and multi-objective optimization are studied. Fluctuation in inter-period blending processing rate is significantly reduced. Graphical abstract: Image, graphical abstract Abstract: Gasoline blending is an important downstream operation in the refinery. The operation is susceptible to uncertainties such as fluctuation in component quality, fluctuation in demand, and a combination of both. These problems naturally involve multiple objectives and non-linear terms corresponding to the mixing of the components for which the genetic algorithm-based approach is more suitable compared to traditional mathematical programming. In this study, such graphical genetic algorithm-based reactive scheduling approach is developed which can handle dynamic changes in component quality and demand as an additional layer of decision making over the nominal scheduling. Three industrial-scale examples are solved using the developed approach for both single- and two-objective optimizations while handling the uncertainty of 10% increase in demand and 5% decrease in component quality. In single-objective optimization, the production cost is minimized whereas in two-objective optimization additionally the fluctuation in blending processing rate is minimized.