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Multiple Criteria in a Top Gas Recycling Blast Furnace Optimized through a k ‐Optimality‐Based Genetic Algorithm
Author(s) -
Mohanty Kaibalya,
Mitra Tamoghna,
Saxén Henrik,
Chakraborti Nirupam
Publication year - 2016
Publication title -
steel research international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.603
H-Index - 49
eISSN - 1869-344X
pISSN - 1611-3683
DOI - 10.1002/srin.201500359
Subject(s) - blast furnace , context (archaeology) , blast furnace gas , reduction (mathematics) , genetic algorithm , mathematical optimization , evolutionary algorithm , flow (mathematics) , computer science , algorithm , mathematics , materials science , metallurgy , paleontology , geometry , biology
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 CO 2 reduction challenges faced by the steel industries today.