An implementation of a multiobjective genetic algorithm (originally based on Deb's NSGAII) in C/C++ with the following features:
- Mixing of integer and floating point decision variables;
- Deb's nondominated sorting operator;
- Ability to associate properties with decision variable values for use in objective function evaluation;
- Creep Mutation;
- Includes a wrapper for linking to external objective function executables; and
- Displays/prints statistics of the search behaviour.
The GA was orignially designed for water systems, but has proven utility in water resource problems more generally. The code/design has been developed at the University of Adelaide by Wenyan Wu, Holger Maier, Angus Simpson, and Jeffrey Newman. WSMGA - Water System Multiobjective Genetic Algorithm
Publications: Details of the algorithm are given in the following paper, which should be cited when the algorithm is used:
Wu W., Simpson A.R. and Maier H.R. (2010) Accounting for greenhouse gas emissions in multi-objective genetic algorithm optimization of water distribution systems, Journal of Water Resources Planning and Management, 136(2), 146-155, DOI: 10.1061/(ASCE)WR.1943-5452.0000020.
The algorithm has been used in the following papers:
Wu W., Maier H.R. and Simpson A.R. (2010) Single-objective versus multi-objective optimisation of water distribution systems accounting for greenhouse gas emissions by carbon pricing, Journal of Water Resources Planning and Management, 136(5), 555-565, DOI: 10.1061/(ASCE)WR.1943-5452.0000072.
Wu W., Maier H.R. and Simpson A.R. (2011) Surplus power factor as a network resilience measure for incorporating hydraulic reliability considerations into water transmission system optimization, Journal of Water Resources Planning and Management, 137(6), 542-546, DOI:10.1061/(ASCE)WR.1943-5452.0000138.
Wu W., Simpson A.R, Maier H.R. and Marchi A. (2012) Incorporation of variable-speed pumping in multiobjective genetic algorithm optimization of the design of water transmission systems, Journal of Water Resources Planning and Management, 138(5), 543–552, DOI: 10.1061/(ASCE)WR.1943-5452.000019.
Wu W., Simpson A.R and Maier H.R. (2012) Sensitivity of optimal tradeoffs between cost and greenhouse gas emissions for water distribution systems to electricity tariff and generation, Journal of Water Resources Planning and Management, 138(2), 182-186, DOI: 10.1061/(ASCE)WR.1943-5452.0000169.
Wu W., Maier H.R. and Simpson A.R. (2013) Multiobjective optimization of water distribution systems accounting for economic cost, hydraulic reliability and greenhouse gas emissions, Water Resources Research, 49(3), 1211-1225, doi:10.1002/wrcr.20120.
Paton F.L., Maier H.R. and Dandy G.C. (2014) Including adaptation and mitigation responses to climate change in a multi-objective evolutionary algorithm framework for urban water supply systems incorporating GHG emissions, Water Resources Research, 50(8), 6285-6304, DOI:10.1002/2013WR015195.
Beh E.H.Y, Maier H.R. and Dandy G.C. (2015) Adaptive, multi-objective optimal sequencing approach for urban water supply augmentation under deep uncertainty, Water Resources Research, 51(3), 1529-1551, DOI:10.1002/2014WR016254.
Beh E.H.Y, Maier H.R. and Dandy G.C. (2015) Scenario driven optimal sequencing under deep uncertainty, Environmental Modelling and Software, 68, 181-195, DOI:10.1016/j.envsoft.2015.02.006.