SPATIAL URBAN LAND USE PLANNING USING MULTI-OBJECTIVE OPTIMIZATION AND GENETIC ALGORITHM
Keywords:
Key physical characteristics’ factors, freight transportation routing, Delphi method, fuzzy analytic hierarchy processAbstract
Urban planning requires not only estimating and locating the future urban extent but also balancing planning aspects to achieve objectives and comply with constraints. The better planning should be able to compromise the multiple conflicting demands from different aspects. The aim of this study focuses on developing and simulating a procedure for optimal urban class planning using Genetic algorithm and Multi-objectives decision analysis (GA-MODA) in plot level. Resulting plans of 2016 were compared to existing land use. The methods were employed to operate on 2 case areas which were selected from a part of Nakhon Ratchasima town. GA-MODA process was applied to generating a number of representative plans that meet the requirement of 6 given objectives and 7 constraints. The objectives cover sufficient housing, employment, open green area, high compatibility, and minimized changing cost and travel rate. For better living, constraints were setup to comply with suggested areas and population densities of urban classes. GA-MODA process resulted in 26 and 370 plans for case areas. These plans were compared to existing land use. The comparison revealed that constraint compliance, being at Pareto front, and sums of normalized objective values (SNOV) of GA-MODA plans are better than of existing land use. It indicates that GA-MODA urban planning is a capable method to generate a number of optimal plans which can provide a better quality of living than existing land use.
References
Aerts, J.C.J.H., Eisinger, E., Heuvelink, G.B.M., and Stewart, T.J. (2003). Using linear integer programming for multi-site land use allocation. Geogr. Anal., 35(2):148-169.
Balling, R.J. (2002). The maximin fitness function for multiobjective evolutionary optimization. In: Optimization in Industry. Parmee, I. C., and Hajela, P.Z. Springer, London, p. 135-147.
Balling, R., Powell, B., and Saito, M. (2004). Generating future land use and transportation plans for high-growth cities using a genetic algorithm. Comput. Aided. Civ. Infrastruct. Eng., 19:213-222.
Cao, K., Batty, M., Huang, B., Liu, Y., Yu, L., and Chen, J.F. (2011). Spatial multi-objective land use optimization: extensions to the non-dominated sorting genetic algorithm-II. Int. J. Geogr. Inform. Sci., 25(12):1949-1969.
Cao, K., Huang, B., Wang, S., and Lin, H. (2012). Sustainable land use optimization using Boundary-based Fast Genetic Algorithm. Comput. Environ. Urban. Syst., 36(3):257-269.
Cherdchai, S. and Mayor, L. (2001). First Meeting of the Kitakyushu Initiative Network (sessionIII): Urban Sustainable Development in Nakhon Ratchasima and Implementation of Pilot Project of the Kitakyushu Initiative. Japan: UNESCAP. Available from: https://kitakyushu.iges.or.jp/docs/network_meetings/ kin1/Presentations/Session%20III/Korat%201.doc. Accessed date: May 20, 2017.
Department of Public Works and Town & Country Planning. (2006). Criteria and Standard of Comprehensive Planning 2549 B.E. Department of Public Works and Town & Country Planning, Bangkok, 134p. (In Thai)
Gen, M. and Cheng, R. (2000). Genetic algorithms and engineering optimization. John Wiley & Sons, New York, 495p.
Guldmann, J. M. (1979). Urban land use allocation and environmental pollution control: An intertemporal optimization approach. Soc. Econ. Plann. Sci., 13(2):71-86.
Hopkins, L. D. (1977). Land use plan design: quadratic assignment and central-facility models. Environ. Plann., 9(6):625-642.
Huang, B. and Zhang, W. (2014). Sustainable land use planning for a downtown lake area in central China: Multiobjective optimization approach aided by urban growth modeling. J. Urban. Plann. Dev., 140(2):1-12.
Huang, G. and Xia, J. (2001). Barriers to sustainable water-quality management. J. Environ. Manage., 61(1):1-23.
Ligmann, Z. A., Church, R. L., and Jankowski, P. (2008). Spatial optimization as a generative technique for sustainable multiobjective land use allocation. Int. J.Geogr. Inform. Sci., 22(6):601-622.
Los, M. (1978). Simultaneous optimization of land use and transportation - A synthesis of the quadratic assignment problem and the optimal network problem. Reg. Sci. Urban. Econ., 8(1):21-42.
Malczewski, J. and Rinner, C. (2015). Multicriteria Decision Analysis in Geographic Information Science. 1st ed. Springer, New York, 331p.
Phisut Technology Company Limited and P&C Management Company Limited. (2010). Muang Nakhon Ratchasima Comprehensive Planning (3rd revised edition): Meeting documents of Nakhon Ratchasima Town Planning Advisory Board, Public Works and Town and Country Planning Nakhon Ratchasima Provincial Office. (In Thai)
Smith, M. J., Goodchild, M. F., and Longley, P. A. (2007). Geospatial Analysis: A Comprehensive Guide to Principle, Techniques and Software Tools. 2nd ed. Troubador, Leicester, 516p.
Stewart, T. J., Janssen, R., and Herwijnen, M. V. (2004). A genetic algorithm approach to multiobjective land use planning. Comput. Oper. Res., 31:2293-2313.
Zhang, W. (2014). Multi-objective optimization for spatial planning of land use in Shenzhen, [Ph.D. thesis]. Department of Geography and Resource Management, Faculty of Social Science, The Chinese University of Hong Kong, Hong Kong. 184p.
