A differentiating evolutionary computation approach for the multidimensional knapsack problem

Authors:
Meysam Mohagheghi Fard;Yoon-Teck Bau;Chien-Le Goh
Affiliations:
Faculty of Computing and Informatics, Multimedia University, Persiaran Multimedia, Cyberjaya, Malaysia;Faculty of Computing and Informatics, Multimedia University, Persiaran Multimedia, Cyberjaya, Malaysia;Faculty of Computing and Informatics, Multimedia University, Persiaran Multimedia, Cyberjaya, Malaysia
Venue:
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
Year:
2012

Citing 3
Cited 0

A Genetic Algorithm for the Multidimensional Knapsack Problem

Journal of Heuristics
A Heuristic Genetic Algorithm Based on Schema Replacement for 0-1 Knapsack Problem

ICGEC '10 Proceedings of the 2010 Fourth International Conference on Genetic and Evolutionary Computing
A fast and elitist multiobjective genetic algorithm: NSGA-II

IEEE Transactions on Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, the DEC (Differentiating Evolutionary Computation) algorithm is presented for solving a zero-one multidimensional knapsack problem. It has three new improvements. They are the use of a chromosome bank for elitism, the use of the superior clan and the inferior clan to improve exploitation and exploration, and the use of genetic modification to enable faster convergence. The experimental results have shown that the DEC algorithm is better than a greedy algorithm and a generic genetic algorithm. It can find solutions very close to those found by the algorithm proposed by Chu & Beasley.