Multiple Criteria in a Top Gas Recycling Blast Furnace Optimized through a  k ‐Optimality‐Based Genetic Algorithm | Zendy

Mohanty Kaibalya | Zendy; Mitra Tamoghna | Zendy; Saxén Henrik | Zendy; Chakraborti Nirupam | Zendy

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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.

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