Skip to main content
padlock icon - secure page this page is secure

Modified Binary Particle Swarm Optimization for Multidimensional Knapsack Problem

Buy Article:

$106.34 + tax (Refund Policy)

This paper presents a modified binary particle swarm optimization for multidimensional knapsack problem using genotype-phenotype concept and mutation operator of genetic algorithms. Computational results show that the modified binary particle swarm optimization is capable of obtaining high-quality solutions for problems of various characteristics. Computational results also show that the modified binary particle swarm optimization is superior to the original binary particle swarm optimization.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: Modified Binary Particle Swarm Optimization; Multidimensional Knapsack Problem

Document Type: Research Article

Affiliations: 1: School of Information and Communication Convergence Engineering, Mokwon University, Daejeon, 35349, Korea 2: Department of Information and Communication Engineering, Myongji University, Gyeonggi-do, Korea

Publication date: November 1, 2016

More about this publication?
  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more