Improved continuous-time model for gasoline blend scheduling |
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| Affiliation: | 1. Department of Automation and Systems Engineering, Federal University of Santa Catarina, Florianópolis, Brazil;2. Department of Chemical Engineering, University of São Paulo, São Paulo, Brazil;3. Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, USA;1. Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau;2. Institute of Physical Internet, Jinan University (Zhuhai Campus), Zhuhai 519070, China;3. School of International Business Administration, Jinan University (Zhuhai Campus), Zhuhai 519070, China;1. Centro de Matemática Aplicações Fundamentais e Investigação Operacional, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal;2. Center for Advanced Process Decision-Making, Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA |
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| Abstract: | This work introduces a reduced-size continuous-time model for scheduling of gasoline blends. Previously published model has been modified by (i) introducing new model features (penalty for deliveries in order to reduce sending material from different product tanks to the same order, product and blender-dependent minimum setup times, maximum delivery rate from component tanks, threshold volume for each blend), (ii) by reducing the number of integer variables, and (iii) by adding lower bounds on the blend and switching costs, which significantly improve convergence. Nonlinearities are introduced by ethyl RT-70 equations for octane blending. Medium-size linear problems (two blenders, more than 20 orders, 5 products) are solved to optimality within one or two minutes. Previously unsolved large scale blending problems (more than 35 orders, 5 product, 2 or 3 blenders) have also been solved to less than 0.5% optimality gap. |
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| Keywords: | Gasoline blend scheduling Continuous-time model Reduced number of discrete variables Nonlinear blending models |
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