Dynamic dual bin packing using fuzzy objectives

Tómas Philip Runarsson*, Magnus Thor Jonsson, Pall Jensson

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

5 Citations (Scopus)

Abstract

This paper presents the use of genetic algorithms (GA) for solving the dual bin packing problem using fuzzy objectives. In bin packing problems, a list, L of items is to be packed into a minimum number of bins. In dual bin packing the items are packed into a maximum number of bins, assuring a minimum weight for each bin. We consider a class which we call 'dynamic dual bin packing'. Similar to the on-line algorithms, the items must be packed sequentially, however seeing more than one item at a time. The number of bins being packed at any time is fixed. A bin is replaced by an empty one, as soon as it is filled. A GA is presented to solve this problem. The results show that the fuzzy packing scheme is essential to solving the problem, and due to the nature of the problem the GA behaves closely to that of a micro-GA.

Original languageEnglish
Pages219-222
Number of pages4
Publication statusPublished - 1996
EventProceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96 - Nagoya, Jpn
Duration: 20 May 199622 May 1996

Conference

ConferenceProceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96
CityNagoya, Jpn
Period20/05/9622/05/96

Fingerprint

Dive into the research topics of 'Dynamic dual bin packing using fuzzy objectives'. Together they form a unique fingerprint.

Cite this