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.
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.
