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Differential Evolution: An Updated Survey

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Book cover Complex, Intelligent, and Software Intensive Systems (CISIS 2018)

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

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Abstract

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.

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Author information

Authors and Affiliations

  1. COMSATS Institute of Information Technology, Islamabad, 44000, Pakistan

    Nadeem Javaid

Authors
  1. Nadeem Javaid
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Correspondence to Nadeem Javaid .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology , Fukuoka, Japan

    Leonard Barolli

  2. Department of Computer Science, COMSATS Institute of Information Technology , Islamabad, Pakistan

    Nadeem Javaid

  3. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology , Fukuoka, Japan

    Makoto Ikeda

  4. Department of Advanced Sciences, Hosei University , Tokyo, Japan

    Makoto Takizawa

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Javaid, N. (2019). Differential Evolution: An Updated Survey. In: Barolli, L., Javaid, N., Ikeda, M., Takizawa, M. (eds) Complex, Intelligent, and Software Intensive Systems. CISIS 2018. Advances in Intelligent Systems and Computing, vol 772. Springer, Cham. https://doi.org/10.1007/978-3-319-93659-8_62

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