895
Views
24
CrossRef citations to date
0
Altmetric
Articles

Optimal spatial allocation of water resources based on Pareto ant colony algorithm

, &
Pages 213-233 | Received 01 Jun 2013, Accepted 25 Sep 2013, Published online: 29 Oct 2013

References

  • Aerts, J.C.J.H. and Heuvelink, G.B.M., 2002. Using simulated annealing for resource allocation. International Journal of Geographical Information Science, 16 (6), 571–587.
  • Azzag, H., et al., 2007. A hierarchical ant based clustering algorithm and its use in three real-world applications. European Journal or Operational Research, 179, 906–922.
  • Blum, C., 2005. Ant colony optimization: introduction and recent trends. Physics of Life Reviews, 2, 353–373.
  • Cai, X., McKinney, D.C., and Lasdon, L.S., 2001a. Solving nonlinear water management models using a combined genetic algorithm and linear programming approach. Advances in Water Resources, 24, 667–676.
  • Cai, X., McKinney, D.C., and Lasdon, L.S., 2001b. Piece-by-piece approach to solving large nonlinear water resources management models. Journal of Water Resources Planning and Management, ASCE, 127 (6), 363–368.
  • Chaharsooghi, S.K. and Amir, H.M.K., 2008. An effective ant colony optimization algorithm (ACO) for multi-objective resource allocation problem (MORAP). Applied Mathematics and Computation, 200 (1), 167–177.
  • Chen, X.H., et al., 2006. Optimal allocation of water resources in Guangzhou City, South China. Journal of Environmental Science and Health, 41 (7), 1405–1419.
  • Chen, Y.M., et al., 2010a. An agent-based model for optimal land allocation (AgentLA) with a contiguity constraint. International Journal of Geographical Information Science, 24 (8), 1269–1288.
  • Chen, Y., Yu, J., and Khan, S., 2010b. Spatial sensitivity analysis of multi-criteria weights in GIS-based land suitability evaluation. Environmental Modelling & Software, 25, 1582–1591.
  • Chen, Y., Yu, J., and Khan, S., 2013. The spatial framework for weight sensitivity analysis in AHP-based multi-criteria decision making. Environmental Modelling & Software, 48, 129–140.
  • Coloni, A. and Dorigo, M.M.V., 1996. Ant system: optimization by a colony of cooperating agent. IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, 26 (l), 29–34.
  • Doerner, K., et al., 2004. Pareto ant colony optimization: a metaheuristic approach to multiobjective portfolio selection. Annals of Operations Research, 131 (1), 79–99.
  • Dorigoa, M. and Blum, C., 2005. Ant colony optimization theory: a survey. Theoretical Computer Science, 344 (3), 243–278.
  • Eckart, Z., Kalyanmoy, D., and Lothar, T., 2000. Comparison of multi-objective evolutionary algorithms: empirical results. Evolutionary Computation, 8 (2), 173–195.
  • Gu, J.J., et al., 2013. Interval multistage joint-probabilistic integer programming approach for water resources allocation and management. Journal of Environmental Management, 128, 615–624.
  • Guo, P., et al., 2010. A two-stage programming approach for water resources management under randomness and fuzziness. Environmental Modelling & Software, 25, 1573–1581.
  • Haddad, O.B., Afshar, A., and Marino, M.A., 2006. Honey-bees mating optimization (HBMO) algorithm: a new heuristic approach for water resources optimization. Water Resources Management, 20 (5), 661–680.
  • Haddad, O.B. and Marino, M.A., 2007. Dynamic penalty function as a strategy in solving water resources combinatorial optimization problems with honey-bee mating optimization (HBMO) algorithm. Journal of Hydroinformatics, 9 (3), 233–250.
  • Hou, J.W., 2013. Spatial assessment for groundwater quality based on GIS and improved fuzzy comprehensive assessment with entropy weights. Chinese Journal of Population Resources and Environment. doi: 10.1080/10042857.2013.800384.
  • Huang, K.N., et al., 2013. An improved artificial immune system for seeking the Pareto front of land-use allocation problem in large areas. International Journal of Geographical Information Science, 27 (5), 922–946.
  • Jalali, M.R., Afshar, A., and Marino, M.A., 2007. Multi-colony ant algorithm for continuous multi-reservoir operation optimization problem. Water Resources Management, 21, 1429–1447.
  • Kelly, B. and Aris, G., 2007. Optimization and assessment of agricultural water-sharing scenarios under multiple socioeconomic objectives. Journal of Water Resources Planning and Management, 133 (3), 264–274.
  • Kumar, D.N. and Reddy, M.J., 2006. Ant colony optimization for multi-purpose reservoir operation. Water Resources Management, 20, 879–898.
  • Labadie, J.W., 2004. Optimal operation of multireservoir systems: state of-the-art review. Journal of Water Resources Planning and Management, 130 (2), 93–111.
  • Li, Y.P., et al., 2008. IFMP: Interval-fuzzy multistage programming for water resources management under uncertainty. Resources, Conservation and Recycling, 52, 800–812.
  • Li, Y.P., et al., 2009. A multistage fuzzy-stochastic programming model for supporting sustainable water-resources allocation and management. Environmental Modelling & Software, 24, 786–797.
  • Li, Y.P. and Huang, G.H., 2009. Fuzzy-stochastic-based violation analysis method for planning water resources management systems with uncertain information. Information Sciences, 179, 4261–4276.
  • Li, Y.P., Huang, G.H., and Nie, S.L., 2010. Planning water resources management systems using a fuzzy-boundary interval-stochastic programming method. Advances in Water Resources, 33, 1105–1117.
  • Li, X., He, J.Q., and Liu, X.P., 2009. Ant intelligence for solving optimal path-covering problems with multi-objectives. International Journal of Geographical Information Science, 23 (7), 839–857.
  • Li, X., He, J.Q., and Liu, X.P., 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.
  • Liu, X.P., et al, 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.
  • Lu, H.W., Huang, G.H., and He, L., 2010. Development of an interval-valued fuzzy linear-programming method based on infinite a – cuts for water resources management. Environmental Modelling & Software, 25, 354–361.
  • Madadgar, S. and Afshar, A., 2008. An improved continuous ant algorithm for optimization of water resources problems. Water Resources Management, 23 (10), 2119–2139.
  • Maier, H.R., et al., 2003. Ant colony optimization for design of water distribution systems. Journal of Water Resources Planning and Management ASCE, 129, 200–209.
  • McKinney, D.C., and Tsai, H.L., 1996. Multigrid methods in GIS grid-cell-based modeling environment. Journal Computing in Civil Engineering, ASCE, 10 (1), 25–30.
  • McKinney, D.C., and Cai, X., 2002. Linking GIS and water resources management models: an object-oriented method. Environmental Modeling and Software, 17 (5), 413–425.
  • McKinney, D.C., et al., 2006. Stochastic optimization of the highland lakes system in Texas. Journal of Water Resources Planning and Management, 132 (2), 62–70.
  • Michael, J.B.K., Jean-Bernard, B., and Laurent, K., 2000. Ant-like task allocation and recruitment in cooperative robots. Nature, 406 (31), 992–995.
  • Pei, T., et al., 2011. Detecting arbitrarily shaped clusters using ant colony optimization. International Journal of Geographical Information Science, 25 (10), 1575–1595.
  • Reddy, M.J. and Kumar, D.N., 2009. Performance evaluation of elitist-mutated multi-objective particle swarm optimization for integrated water resources management. Journal of Hydroinformatics, 11 (1), 79–88.
  • Schluter, M., et al., 2005. Optimizing long-term water allocation in the Amudarya river delta – a water management model for ecological impact assessment. Environmental Modeling and Software, 20 (5), 529–545.
  • Shi, M.J., Tao, W.C., and Zhao, X.T., 2010. A GIS-based bio-economic model applied in water resource management in Shiyang River Basin, Gansu Province, China. Sustainability in Food and Water, Alliance for Global Sustainability Bookseries, 18, 61–71.
  • Tharme, R.E., 2003. A global perspective on environmental flow assessment: emerging trends in the development and application of environmental flow methodologies for rivers. River Research and Applications, 19, 397–441.
  • Wang, J.F., et al., 2002. An marginal benefit equilibrium model for spatial water allocation. Sciences in China (Series D), 45 (3), 201–210.
  • Wang, J.F., Wu, J.L., and Chen, H.Y., 2004. An optimized spatial-temporal-sectoral allocation model for water resources. Geo Journal, 59 (3), 227–236.
  • Wang, J.F., et al., 2008. Optimal water allocation in arid and semi-arid areas. Water Resources Management, 22, 239–258.
  • Wang, S. and Huang, G.H., 2011. Interactive two-stage stochastic fuzzy programming for water resources management. Journal of Environmental Management, 92, 1986–1995.
  • Wardlaw, R. and Sharif, M., 1999. Evaluation of genetic algorithms for optimal reservoir system operation. Journal of Water Resources Planning and Management, 125 (1), 25–33.
  • Watkins, D.W., et al., 1996. Use of geographic information systems in ground-water flow modeling. Journal of Water Resource Planning and Management. ASCE, 122 (2), 88–96.
  • Watkins, D.W., et al., 2000. A scenario-based stochastic programming model for water supplies from the highland lakes. International Transactions in Operational Research, 7 (3), 211–230.
  • Whiteaker, T.L., et al., 2007. Raster-network regionalization for watershed data processing. International Journal of Geographical Information Science, 21 (3), 341–353.
  • Xiao, N., Bennett, D.A., and Armstrong, M.P., 2002. Using evolutionary algorithms to generate alternatives for multi-objective site-search problems. Environment and Planning A, 34 (4), 639–656.
  • Xie, Y.L., et al., 2013. An inexact two-stage stochastic programming model for water resources management in Nansihu Lake Basin, China. Journal of Environmental Management, 127, 188–205.
  • Yamout, G., and El-Fadel, M., 2005. An optimization approach for multi-sectoral water supply management in the Greater Beirut Area. Water Resources Management, 19 (6), 791–812.
  • Yang, X.H., et al., 2005. Node ordinal encoded genetic algorithm for the optimal allocation of water resources. Progress in Natural Science, 15 (5), 448–452.
  • Yeh, W.W.G., 1985. Reservoir management and operations models: a state-of- the-art review. Water Resources Research, 21, 1797–1818.
  • Yu, J., et al., 2011a. Cellular automata-based spatial multi-criteria land suitability simulation for irrigated agriculture. International Journal of Geographical Information Science, 25 (1), 131–148.
  • Yu, J., Chen, Y., and Wu, J.P., 2011b. Modeling and implementation of classification rule discovery by ant colony optimisation for spatial land-use suitability assessment. Computers, Environment and Urban Systems, 35 (4), 308–319.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.