1. Multiple Criteria in a Top Gas Recycling Blast Furnace Optimized through ak-Optimality-Based Genetic Algorithm
- Author
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Kaibalya Mohanty, Nirupam Chakraborti, Henrik Saxén, and Tamoghna Mitra
- Subjects
Engineering ,Blast furnace ,Factor cost ,business.industry ,Metals and Alloys ,Context (language use) ,02 engineering and technology ,Structural engineering ,Condensed Matter Physics ,Multi-objective optimization ,020501 mining & metallurgy ,Reduction (complexity) ,0205 materials engineering ,Steel mill ,Genetic algorithm ,Materials Chemistry ,Multiple criteria ,Physical and Theoretical Chemistry ,business ,Process engineering - Abstract
A steel plant flow sheet containing a top gas recycling blast furnace is simulated and subjected to multi-objective optimization through an evolutionary approach. A recently proposed k-optimality criterion is used, which allows optimizing a large number of objectives in an evolutionary way, which is difficult to do by other methods. A number of promising optimum results, showing the optimum tradeoffs between several cost factors are identified and analyzed. The results appear to be very significant in the context of CO2 reduction challenges faced by the steel industries today.
- Published
- 2015