Cognitive Computation

, Volume 7, Issue 5, pp 594–608 | Cite as

A Biologically Inspired Modified Flower Pollination Algorithm for Solving Economic Dispatch Problems in Modern Power Systems

  • Hari Mohan Dubey
  • Manjaree PanditEmail author
  • B. K. Panigrahi


Gradient-based traditional algorithms fail to locate optimal solutions for real-world problems with non-differentiable/discontinuous objective functions. But biologically inspired optimization algorithms, due to their unconventional random search capability, provide good solutions within finite time to multimodal and non-convex problems. The search capability of these methods largely depends on their exploration and exploitation potential. This paper presents a modified flower pollination algorithm (MFPA) in which (1) the local pollination of FPA is controlled by a scaling factor and (2) an intensive exploitation phase is added to tune the best solution. The effectiveness of MFPA is tested on some mathematical benchmarks and four large practical power system test cases.


Modified flower pollination algorithm (MFPA) Intensive exploitation phase Biologically inspired (BI) techniques Lévy flight Ramp rate limits (RRL) Prohibited operating zones (POZ) Valve point loading (VPL) effects 


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Hari Mohan Dubey
    • 1
  • Manjaree Pandit
    • 1
    Email author
  • B. K. Panigrahi
    • 2
  1. 1.Department of Electrical EngineeringMadhav Institute of Technology and ScienceGwaliorIndia
  2. 2.Department of Electrical EngineeringIndian Institute of TechnologyHauz KhasIndia

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