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 |