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Open AccessArticle

Optimal Project Planning for Public Rental Housing in South Korea

1
Department of Social Housing, Gyeonggi Urban Innovation Corporation, Suwon 16556, Korea
2
School of Urban Planning & Real Estate Studies, Dankook University, Yongin 16890, Korea
3
College of IT Convergence, Gachon University, Seongnam 13120, Korea
*
Authors to whom correspondence should be addressed.
Sustainability 2020, 12(2), 600; https://doi.org/10.3390/su12020600 (registering DOI)
Received: 22 December 2019 / Revised: 2 January 2020 / Accepted: 13 January 2020 / Published: 14 January 2020
(This article belongs to the Special Issue Sustainability with Optimization Techniques)
Although Korea has made notable progress in the availability of public rental housing, Korea’s public rental housing representing 6.3% of the country’s total housing is still below the 8% OECD average from 2016. The Seoul Metropolitan Area (composed of Seoul City, Incheon City, and Gyeonggi Province) has nearly 50% of the country’s population, but 11% of the nation’s territory, meaning the area suffers from an acute shortage of public rental housing. This is a serious problem which is hampering the sustainability of Korean society in general. We will examine the possibility of improving this public housing problem using certain algorithms to optimize decision making and resource allocation. This study reviews two pioneering studies on optimal investment portfolio for land development projects and optimal project combination for urban regeneration projects, and then optimizes a public housing investment combination to maximize the amount of public rental houses in Gyeonggi province using optimization techniques. Through the optimal investment combination, public rental houses were found to be more efficiently and sustainably planned for the community. View Full-Text
Keywords: public rental house; sustainability; optimal project combination; genetic algorithm; branch & bound method public rental house; sustainability; optimal project combination; genetic algorithm; branch & bound method
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Park, J.H.; Yu, J.-S.; Geem, Z.W. Optimal Project Planning for Public Rental Housing in South Korea. Sustainability 2020, 12, 600.

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