Integrating Gene Expression Programming and Geographic Information Systems for Solving a Multi Site Land Use Allocation Problem
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Copyright: © 2020 Khalid A. Eldrandaly. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Problem statement: Land use planning may be defined as the process of allocating different activities or uses to specific units of area within a region. Multi sites Land Use Allocation Problems (MLUA) refer to the problem of allocating more than one land use type in an area. MLUA problem is one of the truly NP Complete (combinatorial optimization) problems. Approach: To cope with this type of problems, intelligent techniques such as genetic algorithms and simulated annealing, have been used. In this study a new approach for solving MLUA problems was proposed by integrating Gene Expression Programming (GEP) and GIS. The feasibility of the proposed approach in solving MLUA problems was checked using a fictive case study. Results: The results indicated clearly that the proposed approach gives good and satisfactory results. Conclusion/Recommendation: Integrating GIS and GEP is a promising and efficient approach for solving MLUA problems. This research focused on minimizing the development costs and maximizing the compactness of the allocated land use. The optimization model can be extended in the future to maximize also the spatial contiguity of the allocated land use.
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- Multi site land use allocation
- gene expression programming