A genetic algorithm (GA) is a search technique used in computing to find exact or approximate solutions to optimization and search problems. Genetic algorithms are a particular class of evolutionary algorithms that use techniques inspired by evolutionary biology such as inheritance, mutation, selection and crossover. GA is a method for search and optimization based on the process of natural selection and evolution. In this approach, several modifications are done for effective implementation of GA to solve the Electric Power Service Restoration Problem. The GA is suitable for the supply restoration because it is very easy to change constraints or objectives, or apply new ones. The objective function includes all the objectives and constraints required for a practical supply restoration scheme. GA starts with number of solutions to a problem, encoded as a string of status of sectionalizing and tie switches. The status of the switch 1 and 0 has been considered as close and open condition of the switch. The string that encodes each string is chromosome and the set of solutions are termed as population.
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