A New Optimal Solution to Environmentally Constrained Economic Dispatch Using Modified Real Coded Genetic Algorithm

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 199)


This paper presents a novel optimization algorithm for environmentally constrained economic dispatch (ECED) problem using modified real coded genetic algorithm (MRCGA). The ECED problem is formulated as a non-linear constrained multi-objective optimization dilemma satisfying both equality and inequality constraints. The regenerating population procedure is added to the conventional RCGA in order to improve escaping the local minimum solution by a new combination of crossover and mutation technique. To solve ECED problem the predictable RCGA is customized specially by the concept of self adaptation of mutation distribution followed by polynomial mutation approach with arithmetic crossover. To test performance compatibility between them, a six units system is being considered and the better simulation results produce improved solution compare to different methods.


Environmentally Constrained Economic Dispatch (ECED) Modified Real Coded Genetic Algorithm (MRCGA) Improved Crossover and Mutation Combination Multivariate q-Gaussian Distribution Self Adaptation 


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Dept. of Electrical EngineeringCamellia Institute of EngineeringKolkataIndia
  2. 2.Dept. of Power EngineeringJadavpur UniversityKolkataIndia

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