Refinery Profit Planning via Evolutionary Many-Objective Optimization
نویسندگان
چکیده
Evolutionary multi-objective optimization (EMO) found applications in all fields of science and engineering. Chemical engineering discipline is no exception. Literature abounds on EMO with a variety algorithms proposed by few dedicated researchers. The Nondominated Sorting Genetic Algorithm (NSGA-III) the latest addition to family EMO. NSGA-III claims have solved multi many-objective problems up 15 objective functions. On other hand, during last 2 decades, chemical has witnessed many such as NSGA-II. In first-of-its-kind study, this paper exploits power versatility solve four-objective problem occurring refinery profit planning. eminently suitable for class problems. We applied obtained full set pareto solutions problem. also observed that they are dominated when compared FNLGP others. ratio HV/IGD was measure quality run. It can be Engineering.
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ژورنال
عنوان ژورنال: Studies in computational intelligence
سال: 2021
ISSN: ['1860-949X', '1860-9503']
DOI: https://doi.org/10.1007/978-3-030-68291-0_3