Economic load dispatch using a chemotactic differential evolution algorithm

Arijit Biswas, Sambarta Dasgupta, Bijaya K. Panigrahi, V. Ravikumar Pandi, Swagatam Das, Ajith Abraham, Youakim Badr

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations


This paper presents a novel stochastic optimization approach to solve constrained economic load dispatch (ELD) problem using Hybrid Bacterial Foraging-Differential Evolution optimization algorithm. In this hybrid approach computational chemotaxis of BFOA, which may also be viewed as a stochastic gradient search, has been coupled with DE type mutation and crossover of the optimization agents. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints (ramp rate limits) and prohibited operating zones. Simulations were performed over various standard test systems with different number of generating units and comparisons are performed with other existing relevant approaches. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques.

Original languageEnglish (US)
Title of host publicationHybrid Artificial Intelligence Systems - 4th International Conference, HAIS 2009, Proceedings
Number of pages9
StatePublished - 2009
Event4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009 - Salamanca, Spain
Duration: Jun 10 2009Jun 12 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5572 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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