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Solving K-Set Partition Problem Using Genetic Algorithm

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dc.contributor.author Ahmed, Md. Shohan
dc.contributor.author Nisha, Tarjia Alam
dc.date.accessioned 2015-12-08T09:09:45Z
dc.date.available 2015-12-08T09:09:45Z
dc.date.issued 12/11/2014
dc.identifier.uri http://dspace.ewubd.edu/handle/2525/1550
dc.description This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering of East West University, Dhaka, Bangladesh. en_US
dc.description.abstract In this paper, we solved K-set partition problem with Genetic algorithm. K-set partition is a problem where we have to partition a given set of numbers into subsets such that their sums are as nearly equal as possible. In other hand, Genetic algorithm (GA) is a particular class of evolutionary algorithm that use techniques inspired by evolutionary biology such as inheritance, mutation, selection, and crossover.GA is implemented as a computer simulation in which a population of abstract representations (called chromosomes or the genotype or the genome) of candidate solutions (called individuals, creatures, or phenotypes) to an optimization problem evolves toward better solutions. We present a GA in conjunction with a specialized heuristic improvement operator for solving K-set partition problem. The performance of our algorithm is evaluated on some set of real-world problems. Computational results show that the genetic algorithm-based heuristic capable of producing high quality solutions. en_US
dc.language.iso en_US en_US
dc.publisher East West University en_US
dc.relation.ispartofseries ;CSE00016
dc.subject Solving K-Set Partition Problem en_US
dc.title Solving K-Set Partition Problem Using Genetic Algorithm en_US
dc.type Technical Report en_US


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