Research Article
Optimal Solutions of Multiproduct Batch Chemical Process Using Multiobjective Genetic Algorithm with Expert Decision System
Table 2
Data used in example 2.
| Processing times, | Unit price for the product ($/Kg) |
| Product | Mixer | Reactor | Extractor | Centrifuge | Product | | | A | 1.15 | 9.86 | 0.4 | 0.5 | A | 0.27 | 0.08 | B | 5.95 | 7.01 | 0.7 | 0.42 | B | 0.29 | 0.10 | C | 3.96 | 6.01 | 0.85 | 0.3 | C | 0.32 | 0.12 | | 0.4 | 0.33 | 0.3 | 0.2 | | | | Product | Size factors (L/kg) | | | | A | 8.28 | 9.7 | 6.57 | 2.95 | | | | B | 5.58 | 8.09 | 6.17 | 3.27 | | | | C | 2.34 | 10.3 | 5.98 | 5.7 | | | | Product | Coefficients | | | | A | 0.2 | 0.24 | 0.4 | 0.5 | | | | B | 0.15 | 0.35 | 0.7 | 0.42 | | | | C | 0.34 | 0.5 | 0.85 | 0.3 | | | | Cost of equipment ($, V in litres) | Minimum size = 250 L | | 250 V0.6 | 250 V0.6 | 250 V0.6 | 250 V0.6 | Maximum size = 10000 L | Operating cost factor () | | | | | 20 | 30 | 15 | 30 | | | |
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