Abstract
Genetic Algorithm (GA) is generating considerable interest for solving industrial optimisation problems. It is proving robust in delivering global optimal solutions and helping to resolve limitations encountered in traditional methods. However there are fewer GA applications in the process optimisation. This paper presents an overview of recent GA applications in process optimisation. The paper explores the features of process optimisation and critically evaluates how current GA techniques are suited for such complex problems. The survey outlines the current status and trends of GA applications in process related industries. For each industry, the paper describes the general domain problem, common issues, current trends, and the improvements generated by adopting the GA strategy. The paper concludes with an outline of future research directions.
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Oduguwa, V., Tiwari, A., Roy, R. (2005). Genetic Algorithm in Process Optimisation Problems. In: Hoffmann, F., Köppen, M., Klawonn, F., Roy, R. (eds) Soft Computing: Methodologies and Applications. Advances in Soft Computing, vol 32. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32400-3_25
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DOI: https://doi.org/10.1007/3-540-32400-3_25
Publisher Name: Springer, Berlin, Heidelberg
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