| 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 |