A GEP-based spatial decision support system for multisite land use allocation

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@Article{Eldrandaly2009,

• author = "Khalid Eldrandaly",
• title = "A GEP-based spatial decision support system for multisite land use allocation",
• journal = "Applied Soft Computing",
• year = "2009",
• volume = "10",
• number = "3",
• pages = "694--702",
• month = jun,
• ISSN = "1568-4946",
• DOI = "doi:10.1016/j.asoc.2009.07.014",
• URL = "http://www.sciencedirect.com/science/article/B6W86-4X2DCVV-2/2/c8addfbfae7f3e5035dc45213f378416",
• keywords = "genetic algorithms, genetic programming, Spatial decision support systems, Multisite land use allocation, GIS, Gene expression programming",
• abstract = "Multisite Land Use Allocation Problem (MLUA) refers to the problem of allocating more than one land use type in an area. MLUA problem is one of the truly NP Complete (combinatorial optimisation) problems. To cope with this type of problems, intelligent techniques such as genetic algorithms, and simulated annealing, have been used. Research in the area of Spatial Decision Support Systems (SDSS) for resource allocation issues, a new scientific area of information system applications developed to support semi-structured or unstructured spatial decisions, has recently generated attention for integrating Artificial Intelligence (AI) techniques with Geographic Information Systems (GIS). In this paper we demonstrate how GIS can be integrated with Gene Expression Programming (GEP), a recently developed AI approach, for solving MLUA problems. The feasibility of the proposed approach in solving MLUA problems was checked using a fictive case study. The results indicated that the proposed approach gives good and satisfactory results.",
• notes = "King Abdulaziz University, P.O. Box 80105, Jeddah 21589, Saudi Arabia",

}

Genetic Programming entries for Khalid Aly Eldrandaly

Citations