Differential Evolution: An Updated Survey

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 772)


Optimization is required every where from science and engineering to decision making in business and implementation in industry. The optimization is desired to achieve a solution with minimum cost and maximum reliability of the system based on the decision variables. Moreover, the decision variables operate within the defined threshold to satisfy the requirements of the objective function. In this regard, evolutionary algorithms are widely accepted in finding near optimal solution. In this study, a survey on differential evolution (DE) scheme has been conducted to highlight its ability in solving optimization problems. The characteristics used by DE to solve single objective optimization problems are given in detail to enlighten the adaptable nature of DE. Moreover, an overview of multi objective optimization problem is also presented to show the qualities of DE in finding near optimal solution. Further, the applications of DE are discussed in multi disciplinary fields. Furthermore, in this paper, we provide critical analysis and unfold the potential future challenges against DE.


Multi-objective Optimization Problem Thyristor Controlled Series Compensator (TCSC) Modified Differential Evolution (MDE) Multifaceted Literature Phosphoric Acid Fuel Cell (PAFCs) 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.COMSATS Institute of Information TechnologyIslamabadPakistan

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