Differential Evolution Algorithm Using Population-Based Homeostasis Difference Vector

  • Shailendra Pratap SinghEmail author
  • Anoj Kumar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 553)


For the last two decades, the differential evolution is considered as one of the powerful nature inspired algorithm which is used to solve real-world problems. DE takes minimum number of function evaluations to reach close to global optimum solution. The performance is very good, but it suffers from the problem of stagnation when tested on multi-modal functions. In this paper, the population-based homeostasis difference vector strategy has been used to improve the performance of differential evolution algorithms. Here we propose two independent difference random vectors named as best difference vector and random difference vector which helps in avoiding stagnation problem of multi-modal functions. The performance of proposed algorithm is compared with other state-of-the-art algorithms on COCO (Comparing Continuous Optimizers) framework. The result verifies that our proposed population-based homeostasis difference vector strategy outperform most of the state-of-the-art DE variants.


Differential evolution algorithm Homeostasis COCO platform 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringMotilal Nehru National Institute of Technology AllahabadAllahabadIndia

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