Greedy continuous particle swarm optimisation algorithm for the knapsack problems
by Xianjun Shen; Yanan Li; Caixia Chen; Jincai Yang; Dabin Zhang
International Journal of Computer Applications in Technology (IJCAT), Vol. 44, No. 2, 2012

Abstract: Knapsack problem is a classical combinatorial optimisation problem. This paper presents greedy continuous particle swarm optimisation (GCPSO) algorithm to solve the knapsack problem. First, the greedy strategy is introduced into the process of particles' initialisation based on standard particle swarm optimisation (SPSO). This strategy guarantees the particle swarm has a better beginning in a degree. Second, based on the analysis of the characteristics of the knapsack problem's solution space, and in terms of the binary code in evolutionary computation, the paper presents multi-state coding. To some extent, the multi-state coding reduces the data redundancy when encoding the solution of the knapsack problem. In experiments, the authors used discrete particle swarm algorithm as well as continuous particle swarm algorithm to find solutions for the knapsack problem. The experimental results show that the GCPSO algorithm provides better solution for the knapsack problems.

Online publication date: Mon, 20-Aug-2012

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Applications in Technology (IJCAT):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com