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Article

A comparison of three heuristic optimization algorithms for solving the multi-objective land allocation (MOLA) problem

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Pages 19-31 | Received 16 Aug 2017, Accepted 27 Dec 2017, Published online: 17 Jan 2018

References

  • Aerts, J. C. J. H., E. Eisinger, G. B. M. Heuvelink, and T. Stewart. J.  2003. “Using Linear Integer Programming for Multi-Site Land-Use Allocation.” Geographical Analysis 35 (2): 148–169. 10.1111/j.1538-4632.2003.tb01106.x.
  • Aerts, J. C. J. H., and G. B. M. Heuvelink. 2002. “Using Simulated Annealing for Resource Allocation.” International Journal of Geographical Information Science 16 (6): 571–587. 10.1080/13658810210138751.
  • Banks, A., J. Vincent, and C. Anyakoha. 2007. “A Review of Particle Swarm Optimization. Part I: Background and Development.” Natural Computing 6 (4): 467–484. doi:10.1007/s11047-007-9049-5.
  • Cao, K., M. Batty, B. Huang, Y. Liu, L. Yu, and J. Chen. 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. doi:10.1080/13658816.2011.570269.
  • Cao, K., B. Huang, S. Wang, and H. Lin. 2012. “Sustainable Land Use Optimization Using Boundary-Based Fast Genetic Algorithm.” Computers, Environment and Urban Systems 36 (3): 257–269. doi:10.1016/j.compenvurbsys.2011.08.001.
  • Chen, D., C. Lee, C.-H. Park, and P. Mendes. 2007. “Parallelizing Simulated Annealing Algorithms Based on High-Performance Computer.” Journal of Global Optimization 39 (2): 261–289. doi:10.1007/s10898-007-9138-0.
  • Coello, C. A. C., G. B. Lamont, and D. A. Van Veldhuizen. 2007. Evolutionary Algorithms for Solving Multi-Objective Problems. Vol. 5. New York: Springer.
  • Datta, D., K. Deb, C. M. Fonseca, F. G. Lobo, P. A. Condado, and J. Seixas. 2007. “Multi-Objective Evolutionary Algorithm for Land-Use Management Problem.” International Journal of Computational Intelligence Research 3 (4): 371–384. 10.5019/j.ijcir.2007.118.
  • Deb, K., S. Agrawal, A. Pratap, and T. Meyarivan. 2000. “A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II.” Lecture Notes in Computer Science 1917: 849–858.
  • Duh, J. D., and D. G. Brown. 2005. “Generating Prescribed Patterns in Landscape Models.” In GIS, Spatial Analysis and Modeling, Eds. D. J. Maguire and M. F. Goodchild, 423–444, ESRI Press.
  • Duh, J. D., and D. G. Brown. 2007. “Knowledge-Informed Pareto Simulated Annealing for Multi-Objective Spatial Allocation.” Computers, Environment and Urban Systems 31 (3): 253–281. 10.1016/j.compenvurbsys.2006.08.002.
  • Eastman, J. R., H. Jiang, and J. Toledano. 1998. Multi-criteria and multi-objective decision making for land allocation using GIS. In Multicriteria Analysis for Land-Use Management. Environment & Management, vol 9, edited by E. Beinat and P. Nijkamp. Dordrecht: Springer. doi:10.1007/978-94-015-9058-7_13.
  • Greenhalgh, D., and S. Marshall. 2000. “Convergence Criteria for Genetic Algorithms.” SIAM Journal on Computing 30 (1): 269–282. doi:10.1137/S009753979732565X.
  • Grefenstette, J. J. 1986. “Optimization of Control Parameters for Genetic Algorithms.” IEEE Transactions on Systems, Man, and Cybernetics 16 (1): 122–128. doi:10.1109/TSMC.1986.289288.
  • Haupt, R. L. (2000). Optimum Population Size and Mutation Rate for a Simple Real Genetic Algorithm That Optimizes Array Factors. In Antennas and Propagation Society International Symposium, 2000. IEEE (Vol. 2, pp. 1034–1037).
  • Hesser, J., and R. Männer (1990). Towards an Optimal Mutation Probability for Genetic Algorithms. In International Conference on Parallel Problem Solving from Nature (pp. 23–32).
  • Kirkpatrick, S., C. D. Gelatt, and M. P. Vecchi. 1983. “Optimization by Simulated Annealing.” Science 220 (4598): 671–680. doi:10.1126/science.220.4598.671.
  • Kitayama, S., and K. Yasuda. 2006. “A Method for Mixed Integer Programming Problems by Particle Swarm Optimization.” Electrical Engineering in Japan 157 (2): 40–49. doi:10.1002/(ISSN)1520-6416.
  • Laskari, E. C., K. E. Parsopoulos, and M. N. Vrahatis (2002). Particle Swarm Optimization for Integer Programming. Proceedings of the 2002 Congress on Evolutionary Computation. CEC’02 (Cat. No.02TH8600), 2, 1582–1587. 10.1109/CEC.2002.1004478
  • Lazoglou, M., P. Kolokoussis, and E. Dimopoulou. 2016. “Investigating the Use of a Modified NSGA-II Solution for Land-Use Planning in Mediterranean Islands.” Journal of Geographic Information System 8 (3): 369–386. doi:10.4236/jgis.2016.83032.
  • Li, X., J. He, and X. Liu. 2009. “Intelligent GIS for Solving High-Dimensional Site Selection Problems Using Ant Colony Optimization Techniques.” International Journal of Geographical Information Science 23 (4): 399–416. doi:10.1080/13658810801918491.
  • Ligmann-Zielinska, A., R. L. Church, and P. Jankowski. 2008. “Spatial Optimization as a Generative Technique for Sustainable Multiobjective Land-Use Allocation.” International Journal of Geographical Information Science 22 (6): 601–622. doi:10.1080/13658810701587495.
  • Liu, X., X. Li, X. Shi, K. Huang, and Y. Liu. 2012. “A Multi-Type Ant Colony Optimization (MACO) Method for Optimal Land Use Allocation in Large Areas.” International Journal of Geographical Information Science 26 (7): 1325–1343. doi:10.1080/13658816.2011.635594.
  • Liu, Y., J. Peng, L. Jiao, and Y. Liu. 2016. “PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules.” PLoS ONE 11 (6): 1–21. 10.1371/journal.pone.0157728.
  • Masoomi, Z., M. S. Mesgari, and M. Hamrah. 2013. “Allocation of Urban Land Uses by Multi-Objective Particle Swarm Optimization Algorithm.” International Journal of Geographical Information Science 27 (3): 542–566. doi:10.1080/13658816.2012.698016.
  • Nourani, Y., and B. Andresen. 1998. “A Comparison of Simulated Annealing Cooling Strategies.” Journal of Physics A: Mathematical and General 31 (41): 8373–8385. doi:10.1088/0305-4470/31/41/011.
  • Onbaşoğlu, E., and L. Özdamar. 2001. “Parallel Simulated Annealing Algorithms in Global Optimization.” Journal of Global Optimization 19 (1): 27–50. doi:10.1023/A:1008350810199.
  • Porta, J., J. Parapar, R. Doallo, F. F. Rivera, I. Santé, and R. Crecente. 2013. “High Performance Genetic Algorithm for Land Use Planning.” Computers, Environment and Urban Systems 37: 45–58. doi:10.1016/j.compenvurbsys.2012.05.003.
  • Sahebgharani, A. 2016. “Multi-Objective Land Use Optimization through Parallel Particle Swarm Algorithm: Case Study Baboldasht District of Isfahan, Iran.” Journal of Urban and Environmental Engineering 10 (1): 42–49. doi:10.4090/juee.
  • Santé, I., F. F. Rivera, R. Crecente, M. Boullón, M. Suárez, J. Porta, and R. Doallo. 2016. “A Simulated Annealing Algorithm for Zoning in Planning Using Parallel Computing.” Computers, Environment and Urban Systems 59: 95–106. 10.1016/j.compenvurbsys.2016.05.005.
  • Santé-Riveira, I., M. Boullón-Magán, R. Crecente-Maseda, and D. Miranda-Barrós. 2008. “Algorithm Based on Simulated Annealing for Land-Use Allocation.” Computers & Geosciences 34 (3): 259–268. 10.1016/j.cageo.2007.03.014.
  • Satty, T. L. 2008. “Relative Measurement and Its Generalization in Decision Making: Why Pair Wise Comparisons Are Central in Mathematics for the Measurement of Intangible factors-The Analytic Hierarchy Process.” Racsam 102 (2): 251–318. doi:10.1007/BF03191825.
  • Singh, G., R. V. Grandhi, and D. S. Stargel. 2010. “Modified Particle Swarm Optimization for a Multimodal Mixed-Variable Laser Peening Process.” Structural and Multidisciplinary Optimization 42 (5): 769–782. doi:10.1007/s00158-010-0540-8.
  • Song, M., and D. Chen. (2017). Establishing a Comprehensive Land Suitability Evaluation System for “Multi-Plan Integration” in China’s County-Level Division. Manuscript submitted for publication.
  • Stewart, T. J., R. Janssen, and M. Van Herwijnen. 2004. “A Genetic Algorithm Approach to Multiobjective Land Use Planning.” Computers & Operations Research 31 (14): 2293–2313. 10.1016/S0305-0548(03)00188-6.
  • Suman, B., and P. Kumar. 2006. “A Survey of Simulated Annealing as A Tool for Single and Multiobjective Optimization on JSTOR.” Journal of the Operational Research Society 1143–1160. 10.1057/palgrave.jors.2602068.
  • Tong, D., and A. T. Murray. 2012. “Spatial Optimization in Geography.” Annals of the Association of American Geographers 102 (6): 1290–1309. doi:10.1080/00045608.2012.685044.

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