A flexible labour division approach to the polygon packing problem based on space allocation
Yingcong Wang,
Renbin Xiao and
Huimin Wang
International Journal of Production Research, 2017, vol. 55, issue 11, 3025-3045
Abstract:
This paper deals with the two-dimensional satellite module polygon packing problem. Based on the duality of material and space, it regards the polygon packing problem as a space allocation problem, which involves allocating the container space to the given polygons reasonably and efficiently. Ant colony’s labour division is essentially a kind of task allocation. Using this task allocation to achieve the space allocation in polygon packing problems, a flexible labour division approach (FLD) is proposed based on the response threshold model. According to the characteristics of space allocation in polygon packing problems, FLD designs three actions for polygons to occupy the container space. With the interaction between environmental stimulus and response threshold, each polygon takes an appropriate action to complete the space allocation and a layout that meets the requirements of satellite module layout is obtained. The results of standard test instances demonstrate the effectiveness of FLD when compared with self-organisation emergence algorithm. Moreover, experiments on the general polygon packing problem also show that FLD is competitive with other existing algorithms.
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2016.1229070 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:55:y:2017:i:11:p:3025-3045
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2016.1229070
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().