A novel greedy quantum inspired cuckoo search algorithm for variable sized bin packing problem
by Abdesslem Layeb; Seriel Rayene Boussalia
International Journal of Mathematics in Operational Research (IJMOR), Vol. 6, No. 6, 2014

Abstract: Bin packing is a well-known NP-hard optimisation problem which has several real applications. Classical bin packing (BPP) is a simple model where all bins are identical. However, the variable sized bin packing problem (VSBPP) is a generalisation of the bin packing problem where bins of different capacities are available for packing a set of items having different weights. The objective is to pack all the items in the bins minimising the sum of the remaining spaces of the used bins. In this paper, we present a new approach based on the quantum inspired cuckoo search algorithm to deal with the variable sized bin packing problem (VSBPP) problem. The contribution consists in defining an appropriate quantum representation based on qubit representation to represent bin packing solutions. The second contribution is a proposition of a new hybrid quantum measure operation which uses first fit heuristic to pack no filled objects by the standard measure operation. The third contribution is the use of a new hybrid randomised heuristic based on both first fit and best heuristics. The obtained results are very encouraging and show the feasibility and effectiveness of the proposed approach.

Online publication date: Fri, 31-Oct-2014

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 Mathematics in Operational Research (IJMOR):
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