Introducing a Developed Meta-heuristic Model based on Multi Objectives Genetics Algorithm for Optimal Land Use Change Modeling


Alaeimoghaddam, Sanaz., Karimi, Mohammad., & Mohammadzadeh, Ali. (2014). "Modeling the allocation of urban utilities using genetics algorithm for non-dominated selection of the reference point", Journal of geomatics science and Technology, No. 4, pp. 47-65 (In Persian).
Cao, K., Batty, M., Huang, B., Liu, Y., Yu, L., & Chen, J. (2011). Spatial multi-objective land use optimization: extensions to the non-dominated sorting genetic algorithm-II. International journal of Geographical Information Science, 25(12), 1949-1969.
Datta, D., Deb, K., Fonseca, C. M., Lobo, F., Condado, P., & Seixas, J. (2007). Multi-objective evolutionary algorithm for land-use management problem. International Journal of computational intelligence research, 3(4), 371-384.
Deb, K., & Sundar, J. (2006). Reference point based multi-objective optimization using evolutionary algorithms. Proceedings of the 8th annual conference on genetic and evolutionary computation, 635-642.
Deb, K., Mohan, M., & Mishra, S. (2005). Evaluating the ε-domination based on multi-objectives evolutionary algorithm for a quick computation of pareto-optimal solutions. Journal of evolutionary computation, 13(4), 501-525. doi: 10.1162/106365605774666895.
Herzig, A. (2008). A GIS-based module for the multi objectives optimization of areal resource allocation. In Friis. Proceedings of the 11th AGILE International Conference on Geographic Information Science, University of Girona, Spain. http://agile. gis. geo. tu-dresden. de/web/Conference_Paper/CDs/AGILE (Vol. 202008).
Krink, T. (2002) Multi objectives landuse optimization using evolutionary algorithms (Doctoral dissertation, Dept of Computer Science, University of Aarhus).
Matkan, Aliakbar., Shakiba, Alireza., Mirbagheri, Babak., Shayegan, Mehran., & Tenasan, Mohammad. (2015). "Designing a user-based optimization model based on Multi-objectives genetics algorithm with land approach (a case study for Roodbar, Southern-Kerman)", Journal of remote sensing and GIS of Iran, No. 1, pp. 39-59 (In Persian).
Nasiri, Esmail. (2009). "Application of Multi-Criteria Decision Making Methods (SMCDM) with GIS in land use", Proceedings of geomatics conference, national cartographic center of Iran. pp. 1-4 (In Persian).
Rafipour-Langeroudi, M., Kerachian, R., & Bazargan-Lari, M. (2014). Developing operating rules for conjunctive use of surface and groundwater considering the water quality issues. Journal of civil engineering, 18(2), 454-461. doi: 10.1007/s12205-014-1193-8.
Saeedian, Bahram., Mesgari, Mohammadsaadi., & Ghodousi, Mostafa. (2015). "A comparative study on the efficiency of meta heuristic genetics and PSO algorithms for water optimal allocation in agricultural farms in the condition of water scarcity". Journal of geospatial information technology. No. 4. pp. 19-42 (In Persian).
Shayegan, Mehran., Alimohammadi, Abbas., & Mansourian, Ali. (2012). "Multi-objectives optimization of landuse allocation using NSGA-II algorithm". Journal of remote sensing and GIS of Iran, No. 2, pp. 18-18 (In Persian).
Sheta, A., & Turabieh, H. (2006). A comparison between genetic algorithms and sequential quadratic programming in solving constrained optimization problems. International Journal on artificial intelligence and machine learning (AIML), 6(1), 67-74.
Sivanandam, S. N., & Deepa, S. N. (2010). Introduction to genetic algorithms. Berlin: Springer.
Stewart, T., Janssen, R., & Herwijnen, M. (2004). A genetic algorithm approach to multi objectives landuse planning. Journal of computers and operations research, 31(14), 2293-2313. doi:10.1016/S0305-0548(03)00188-6.
Tabari, M., Maknoon, R., & Ebadi, T. (n.d.). Multi-objective optimal model for Surface and Ground-water conjunctive use management using SGAs and NSGA-II. Journal of Water and Sewage, 20(1), 2-12.
Villalta-Calderon, C. A., & Pérez-Alegría, L. R. (2010). Multi-objective optimization approach for land use allocation based on water quality criteria. 21st century watershed technology: improving water quality and environment conference proceedings, 21-24 February 2010, Universidad EARTH, Costa Rica (p. 1). American Society of Agricultural and Biological Engineers.
Yang, A., Shan, Y., & Bui, L. T. (Eds.). (2008). Success in Evolutionary Computation (Vol. 92). Springer.
Yeh, J. Y., & Lin, W. S. (2007). Using simulation technique and genetic algorithm to improve the quality care of a hospital emergency department. Journal of expert systems with applications, 32(4), 1073-1083.