Self-adaptive differential evolution with multiple strategies for dynamic optimization of chemical processes

2019 ◽  
Vol 31 (7) ◽  
pp. 2041-2061 ◽  
Author(s):  
Bin Xu ◽  
Wushan Cheng ◽  
Feng Qian ◽  
Xiuhui Huang
Keyword(s):  
Differential Evolution ◽  
Dynamic Optimization ◽  
Chemical Processes ◽  
Multiple Strategies ◽  
Adaptive Differential Evolution ◽  
Self Adaptive

Dynamic optimization using Self-Adaptive Differential Evolution

2009 ◽  
Author(s):  
Janez Brest ◽  
Ales Zamuda ◽  
Borko Boskovic ◽  
Mirjam Sepesy Maucec ◽  
Viljem Zumer
Keyword(s):  
Differential Evolution ◽  
Dynamic Optimization ◽  
Adaptive Differential Evolution ◽  
Self Adaptive

scholarly journals Comparative performance evaluation of self-adaptive differential evolution with GA, SCE and DE algorithms for the automatic calibration of a computationally intensive distributed hydrological model

2020 ◽  
Author(s):  
Saswata Nandi ◽  
M. Janga Reddy
Keyword(s):  
Differential Evolution ◽  
Hydrological Model ◽  
Automatic Calibration ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Infiltration Capacity ◽  
Vic Model ◽  
Adaptive Differential Evolution ◽  
Computationally Intensive ◽  
Self Adaptive

Abstract Recently, physically-based hydrological models have been gaining much popularity in various activities of water resources planning and management, such as assessment of basin water availability, floods, droughts, and reservoir operation. Every hydrological model contains some parameters that must be tuned to the catchment being studied to obtain reliable estimates from the model. This study evaluated the performance of different evolutionary algorithms, namely genetic algorithm (GA), shuffled complex evolution (SCE), differential evolution (DE), and self-adaptive differential evolution (SaDE) algorithm for the parameter calibration of a computationally intensive distributed hydrological model, variable infiltration capacity (VIC) model. The methodology applied and tested for a case study of the upper Tungabhadra River basin in India, and the performance of the algorithms is evaluated in terms of reliability, variability, efficacy measures in a limited number of function evaluations, their ability for achieving global convergence, and also by their capability to produce a skillful simulation of streamflows. The results of the study indicated that SaDE facilitates an effective calibration of the VIC model with higher reliability and faster convergence to optimal solutions as compared to the other methods. Moreover, due to the simplicity of the SaDE, it provides easy implementation and flexibility for the automatic calibration of complex hydrological models.

scholarly journals A face recognition framework using self-adaptive differential evolution

2019 ◽  
Vol 17 (2) ◽  
pp. 4-14
Author(s):  
Guilherme Felippe Plichoski ◽  
Chidambaram Chidambaram ◽  
Rafael Stubs Parpinelli
Keyword(s):  
Face Recognition ◽  
Differential Evolution ◽  
Adaptive Differential Evolution ◽  
Self Adaptive
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