https://nova.newcastle.edu.au/vital/access/manager/Index ${session.getAttribute("locale")} 5 Application of multi objective optimization for managing urban drought security in the presence of population growth https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:11884 Wed 11 Apr 2018 17:07:29 AEST ]]> Comparison of genetic algorithm and ant colony optimization methods for optimization of short-term drought mitigation strategies https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:9001 Wed 11 Apr 2018 16:34:19 AEST ]]> Enhancing the robustness of water resource simulation models based on network linear programming https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:9244 Wed 11 Apr 2018 14:17:34 AEST ]]> Interpretation of cone factor in undrained soils via full-penetration finite-element analysis https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:14293 Wed 11 Apr 2018 11:38:42 AEST ]]> Multiobjective optimization of urban water resources: moving toward more practical solutions https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:17149 Wed 11 Apr 2018 10:35:04 AEST ]]> Application of multiobjective optimization to scheduling capacity expansion of urban water resource systems https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:16957 Wed 11 Apr 2018 10:27:48 AEST ]]> How flexibility in urban water resource decisions helps to manage uncertainty? https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:28935 Tue 01 Aug 2017 13:38:34 AEST ]]> Comparison of multi-objective genetic algorithm with ant colony optimization: a case study for Canberra water supply system https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:8850 Sat 24 Mar 2018 08:39:01 AEDT ]]> Multi-objective optimization analysis for the Canberra water supply system https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:8997 Sat 24 Mar 2018 08:38:41 AEDT ]]> Addressing the shortcomings of water resource simulation models based on network linear programming https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:8918 Sat 24 Mar 2018 08:38:20 AEDT ]]> Application of multiobjective optimization methods for urban water management: a case study for Canberra water supply system https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:8930 Sat 24 Mar 2018 08:37:06 AEDT ]]> Assessment of the replicate compression heuristic to improve efficiency of urban water supply headworks optimization https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:8188 Sat 24 Mar 2018 08:36:15 AEDT ]]> New robust multiobjective ant colony optimization (MOACO) method https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:9243 Sat 24 Mar 2018 08:35:00 AEDT ]]> Robust optimization to secure urban bulk water supply against extreme drought and uncertain climate change https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:21480 Sat 24 Mar 2018 08:03:42 AEDT ]]> Monthly recharge modelling for the Gnangara Mound https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:18598 Sat 24 Mar 2018 08:01:04 AEDT ]]> A monthly network flow program emulator of the PRAMS Gnangara groundwater model https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:17643 Sat 24 Mar 2018 07:57:16 AEDT ]]> A stochastic model for identifying the long term dynamics of indoor household water uses https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:6157 Sat 24 Mar 2018 07:44:32 AEDT ]]> The replicate compression heuristic for improving efficiency of urban water supply headworks optimization https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:6228 Sat 24 Mar 2018 07:44:22 AEDT ]]> Efficient multi-objective optimization methods for computationally intensive urban water resources models https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:27701 ∈MOEA) using two case studies based on the urban water resource systems serving two major Australian cities. The case study problems involved two or three objectives and 10 or 13 decision variables affecting infrastructure investment and system operation. The results show that NSGA-II was the worst performing method. However, none of the remaining methods was unambiguously superior. For example, while EMOACO-I converged more rapidly, its diversity was comparable but not superior to the other methods. Greater differences in performance were found as the number of objectives and case study complexity increased. This suggests that pooling the results from a number of methods could help guard against the vagaries in performance of individual methods.]]> Sat 24 Mar 2018 07:40:10 AEDT ]]> Robust optimization of urban drought security for an uncertain climate https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:27166 Sat 24 Mar 2018 07:31:39 AEDT ]]> Optimisation of Urban Water Supply Headworks Systems Using Probabilistic Search Methods and Parallel Computing https://nova.newcastle.edu.au/vital/access/manager/Repository/uon:685 Fri 23 Mar 2018 17:09:06 AEDT ]]>