Abdel-Ghany, Sarah M. and Ayad, Hany M. and Elcherif, Ingi A. (2022) Sustainable Multi-objective Optimisation in Land-use Planning based on Non-dominated Sorting Genetic Algorithm (NSGA-II): a Case Study in Alexandria, Egypt. Mobility, Knowledge and Innovation Hubs in Urban and Regional Development. Proceedings of REAL CORP 2022, 27th International Conference on Urban Development, Regional Planning and Information Society. pp. 733-744. ISSN 2521-3938
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Text (Sustainable Multi-objective Optimisation in Land-use Planning based on Non-dominated Sorting Genetic Algorithm (NSGA-II): a Case Study in Alexandria, Egypt)
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Abstract
Due to urban sprawling, the world’s land-use patterns have rapidly changed, leading to conflict and competition among urban land-uses. This conflict resulted in a range of inefficient land-use patterns. The negative impacts of such patterns suggest the need to improve the efficiency of land-use planning strategies to support better sustainable development. To attain such efficiency, many researchers have adopted algorithmic approaches perceiving land-use planning as a multi-objective optimization problem. These approaches allow encompassment of the numerous variables and constraints that are introduced in the planning process by decision makers and stakeholders. In this regard, a meta-heuristic method; the Nondominated Sorting Genetic Algorithm (NSGA-II), could provide an efficient decision support tool for landuse planning through offering pareto optimal land-use allocation alternatives. This paper aims at adopting NSGA-II to enhance sustainable land-use planning strategies at a neighborhood scale in the city of Alexandria, Egypt. The research suggests the adaptation of the Constrained Multiobjective Optimization of Land-use Allocation model (CoMOLA) for three main objectives: (i) maximizing the value of economic benefit, (ii) spatial compactness, and (iii) land-use compatibility. Several land-use allocation scenarios are investigated through an iterative process which includes the variables of spatial units’ number, population sizes and significance of allocation objectives. The scenarios are then compared to the existing condition of land-use distribution. The results show that the proposed approach using CoMOLA tool exhibits good potential to support interactive land-use planning processes by searching over multiple plans for optimal sets of non-dominated solutions. The optimized results could provide the scientific basis for defining suitable interventions for improving sustainability measures and spatial optimization of landuses at the neighborhood scale.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Land-use allocation, Non-dominated Sorting Genetic Algorithm (NSGA-II), Multi-objective optimization, Constrained Multi-objective Optimization of Land-use Allocation model (CoMOLA), Land use planning |
| Subjects: | G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography G Geography. Anthropology. Recreation > GB Physical geography |
| Depositing User: | The CORP Team |
| Date Deposited: | 10 Nov 2022 13:54 |
| Last Modified: | 18 Dec 2022 14:20 |
| URI: | http://repository.corp.at/id/eprint/895 |
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