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Chapter 4 Metaheuristics for the optimization of chemical processes

  • Oscar Daniel Lara-Montaño , Manuel Toledano-Ayala , Claudia Gutiérrez-Antonio , Fernando Israel Gómez-Castro , Elena Niculina Dragoi und Salvador Hernández
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Abstract

Metaheuristic optimization algorithms are effective for exploring complex multidimensional search spaces and avoiding convergence on suboptimal local solutions. They are used across a range of chemical engineering applications, from process design and reactor configuration to environmental engineering and energy management. These algorithms are used for adjusting operational parameters and identifying solutions that might not be detected by conventional methods. This chapter reviews the use of metaheuristic algorithms in these areas, referencing recent published works to illustrate their practical benefits. The discussion aims to provide a concise overview of how these algorithms enhance chemical engineering practices, contributing to increased efficiency, adaptability, and sustainability in solutions.

Abstract

Metaheuristic optimization algorithms are effective for exploring complex multidimensional search spaces and avoiding convergence on suboptimal local solutions. They are used across a range of chemical engineering applications, from process design and reactor configuration to environmental engineering and energy management. These algorithms are used for adjusting operational parameters and identifying solutions that might not be detected by conventional methods. This chapter reviews the use of metaheuristic algorithms in these areas, referencing recent published works to illustrate their practical benefits. The discussion aims to provide a concise overview of how these algorithms enhance chemical engineering practices, contributing to increased efficiency, adaptability, and sustainability in solutions.

Heruntergeladen am 6.11.2025 von https://www.degruyterbrill.com/document/doi/10.1515/9783111383439-004/html
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