Land layout optimisation for virtual land sales in the metaverse: two-dimensional assortment problem
Yao-Huei Huang,
Bohan Hu and
F. J. Hwang
International Journal of Production Research, 2025, vol. 63, issue 13, 4617-4638
Abstract:
With the growing popularity of the metaverse, the virtual real estate in the metaverse has generated immense investment enthusiasm. Considering the virtual land sale mode allowing the potential buyers to request the purchase of rectangular land parcels of a specified size, this study investigates how to lay out the requested land parcels for minimising the size of the required rectangular open land, which can be formulated completely as the two-dimensional assortment problem (2DAP). Due to the strong NP-hardness of the 2DAP, an effective and efficient heuristic solution approach named binary adjoining algorithm (BAA) is presented for tackling the 2DAPs in large scales. The conducted computational experiments show that the BAA can outperform the state-of-the-art piecewise-linearisation mixed integer linear programming model as well as four existing advanced metaheuristic techniques designed for the 2DAP, in both solution quality and computational time, on the small-size instances. The superiority of the BAA over either foregoing reference method on the large-size instances with up to 60 requested land parcels is also demonstrated.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2024.2440786 (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:63:y:2025:i:13:p:4617-4638
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2024.2440786
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 ().