Abstract
The fundamental concepts used in this book are described below. To implement the link between any process simulator and metaheuristic techniques, the methodology has been divided in three parts: simulation, optimization, and link software; and the involved concepts are described as follows.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Bibliography
AspenTech. (2015). Aspen Plus User’s Guide, V8.8. s.l.: Aspen Technology Inc.
Coello-Coello, C. A., Van-Veldhuizen, D. A., & Lamont, G. B. (2002). Evolutionary algorithms for solving multi-objective problems. New York, NY: Kluwer Academic.
Devillers, J. (1996). Genetic algorithms in molecular modeling. San Diego, CA: Academic Press.
Guo, H., et al. (2014). Differential evolution improved with self-adaptive control parameters based on simulated annealing. Swarm and Evolutionary Computation, 19, 52–67.
Ouyang, A., et al. (2015). A novel hybrid multi-objective population migration algorithm. International Journal of Pattern Recognition and Artificial Intelligence, 29(01), 1559001.
Sharma, S., & Rangaiah, G. P. (2014). Hybrid approach for multiobjective optimization and its application to process engineering problems. In J. Valadi & P. Siarry (Eds.), Applications of metaheuristics in process engineering (pp. 423–444). s.l.: Springer International Publishing.
Sharma, S., & Rangaiah, G. P. (2016). Mathematical modeling simulation and optimization for process design. In G. P. Rangaiah (Ed.), Chemical process retrofitting and revamping: Techniques and applications (pp. 99–128). Singapore: Wiley.
Wang, X., & Tang, L. (2013). Multiobjective operation optimization of naphtha pyrolysis process using parallel differential evolution. Industrial & Engineering Chemistry Research, 52(40), 14415–14428.
Wong, J. Y., Sharma, S., & Rangaiah, G. P. (2016). Design of shell-and-tube heat exchangers for multiple objectives using elitist non-dominated sorting genetic algorithm with termination criteria. Applied Thermal Engineering, 93, 888–899.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
Ponce-Ortega, J.M., Hernández-Pérez, L.G. (2019). Introduction. In: Optimization of Process Flowsheets through Metaheuristic Techniques . Springer, Cham. https://doi.org/10.1007/978-3-319-91722-1_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-91722-1_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-91721-4
Online ISBN: 978-3-319-91722-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)