Scheduling Gasoline Blending Operations from ... - ACS Publications

Jun 22, 2016 - We thank two recent publications1,2 for noting some issues with discrepancies in the data and results reported in our paper,3 “Schedu...
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Corrections to “Scheduling Gasoline Blending Operations from Recipe Determination to Shipping Using Unit Slots” Jie Li* and I. A. Karimi Ind. Eng. Chem. Res. 2011, 50 (15), 9156−9174 (DOI: 10.1021/ie102321b)

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e thank two recent publications1,2 for noting some issues with discrepancies in the data and results reported in our paper,3 “Scheduling Gasoline Blending Operations from Recipe Determination to Shipping Using Unit Slots” (Ind. Eng. Chem. Res. 2011, 50 (15), 9156−9174). The purpose of this communication is to resolve the issues and present revised data and results. Since the data changes are several and interspersed across several tables, we have revised Tables 1, 2, 3, 5, 6, 7, and 8, and we have added one more table (Table 9), which lists orders that can be supplied from the various product tanks in the examples. The differences from our original paper3 are highlighted in boldface font with a light-orange background color in all tables. For convenience, Table 4 from our original paper3 is also given in this communication. We also present revised schedules in Figure 5. In addition, we wish to state the following assumptions that may not be clear in our paper: • First, the setup times between any two successive blend runs are assumed to be zero in all examples. • Second, the product tanks cannot receive and supply simultaneously in all examples. • Third, the blenders are idle at time zero, except in Example 5, where the blender is processing product P1. • Fourth, the transition cost for each blender from its initial state to the state in the first blend run is assumed to be zero.

All examples were solved using CPLEX 12.6.1.0 in GAMS 24.4.5 on a Dell OPTIPLEX 9020 computer (Intel Xeon CPU 3.00 GHz, 16.0 GB memory) running Linux.



ACKNOWLEDGMENTS



AUTHOR INFORMATION

We gratefully acknowledge Professor Vladimir Mahalec for his helpful discussions and constructive suggestions. We also gratefully acknowledge Professor Christodoulos A. Floudas for providing GAMS software and computing facilities.

Corresponding Author

*E-mail: [email protected], phone: +44 (0) 161 306 8622.



REFERENCES

(1) Castillo-Castillo, P. A.; Mahalec, V. Inventory Pinch Based, Multiscale Models for Integrated Planning and SchedulingPart II: Gasoline Blend Scheduling. AIChE J. 2014, 60 (7), 2475−2497. (2) Cerda, J.; Pautasso, P. C.; Cafaro, D. C. A Cost-Effective Model for the Gasoline Blend Optimization Problem. AIChE J. 2016, in press (DOI: 10.1002/aic.15208).

Table 1. Order Data for Examples (a) 1−9 and (b) 10−14

Published: June 22, 2016 © 2016 American Chemical Society

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DOI: 10.1021/acs.iecr.6b01930 Ind. Eng. Chem. Res. 2016, 55, 7231−7237

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(3) Li, J.; Karimi, I. A. Scheduling Gasoline Blending Operations from Recipe Determination to Shipping Using Unit Slots. Ind. Eng. Chem. Res. 2011, 50 (15), 9156−9174. (4) Li, J.; Karimi, I. A.; Srinivasan, R. Recipe Determination and Scheduling of Gasoline Blending Operations. AIChE J. 2010, 56, 441− 465.

Table 1. continued

Table 2. Product and Component Tank Data for Examples 1−14

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Table 3. Component and Product Property Indices for Examples 1−14

Table 4. Allowable Composition Ranges for Components in Products of Examples 1−14

Table 5. Blender and Economic Data for Examples 1−14

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Table 6. Periods, Durations, Slots, and Feed Rates to Component Tanks for Examples 1−14

Table 7. Solution Statistics of Various Algorithms/Codes for SPM for Examples 1−14a

a Data for all process slots are taken from Li et al.4 The CPU time limits for SPM are 10 800 s for Examples 1−10, 36 000 s for Examples 11 and 12, and 108 000 s for Examples 13 and 14. Those for RSPM are 3600 s for Examples 1−10, and 10 800 s for Examples 11−14. Footnote symbol “η” denotes that the CPU time limit for SPM was reached; footnote symbol “*” denotes that the total CPU time limit for the entire algorithm was reached.

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Table 8. Solution Statistics of Various Algorithms/Codes for MPM for Examples 1−14a

a

Data for all process slots are taken from Li et al.4 The CPU time limits for MPM are 10 800 s for Examples 1−10, 36 000 s for Examples 11 and 12, and 108 000 s for Examples 13 and 14. Those for RSPM are 3600 s for Examples 1−10, and 10 800 s for Examples 11−14. Footnote symbol “η” denotes that the CPU time limit for MPM was reached; footnote symbol “*” denotes that the total CPU time limit for the entire algorithm was reached.

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Table 9. (a) Orders That Can Be Delivered by Product Tanks for Examples (a) 1−9 and (b) 10−14

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Figure 5. (a) Blending schedule for Example 12 (35 orders) from RSPM. (b) Order delivery schedule for Example 12 (35 orders) from RSPM.

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