Using Multiobjective Optimization to Find Optimal Operating Rules for Short-Term Planning of Water Grids

Interpreting a Pareto set of operating options for water grids: a framework and case study

“…In Ashbolt et al (2016), multi-objective simulationoptimisation was applied to the case study using the Source simulation-optimisation software (Dutta et al 2013) to identify operating rules that are optimal in terms of the three management objectives. Source uses the NSGA-II genetic algorithm (Deb et al 2002).…”

“…Source uses the NSGA-II genetic algorithm (Deb et al 2002). Further details of the multi-objective simulation-optimisation process are provided in Ashbolt et al (2016). The result of multi-objective optimisation of the case-study problem was a set of 677 operating options, each of which represents a set of operating rules (Ashbolt et al 2016).…”

“…Further details of the multi-objective simulation-optimisation process are provided in Ashbolt et al (2016). The result of multi-objective optimisation of the case-study problem was a set of 677 operating options, each of which represents a set of operating rules (Ashbolt et al 2016). Each operating option is Pareto-optimal, meaning that none of the operating options are dominated (out-performed) by any of the others in terms of all three objectives of minimising total operational cost, minimising total spill and maximising minimum storage.…”

“…Steps 1-4 of the framework concern the problem formulation and multi-objective simulation-optimisation of operating rules. Steps 2-4 were demonstrated in Ashbolt et al (2016), and the outcome is a Pareto set of operating options such as that presented in Figure 2. Each operating option consists of a set of decision variables that define the operating rules, and which is Pareto-optimal in terms of the management objectives.…”

Inferring efficient operating rules in multireservoir water resource systems: A review

“…,Sun et al (2018) Rule curvesGenetic algorithmsAhmadi Najl, Haghighi, and Vali Samani (2016),Ashbolt et al (2016), Borgomeo, Mortazavi-Naeini,Hall, O'Sullivan, and Watson (2016),Cui and Kuczera (2005),Lerma et al (2013Lerma et al ( , 2015,Zhu, Zhang, Yin, Zhou, and Jiang (2013),Ashbolt and Perera (2018), Rashid, Latif, and Azmat(2018)Particle swarm optimizationGuo, Hu, Zeng, and Li (2013), Shourian et al (2008), Spiliotis et al (2016), Wan et al (2018) Pattern search Celeste and Billib (2009), Sun et al (2018)Radial basis functionsGenetic algorithmsCulley et al (2016),Giuliani, Herman, Castelletti, and Reed (2014),,Giuliani, Li, et al (2016),Giuliani, Quinn, Herman, Castelletti, and Reed (2018)),Salazar et al (2016),Desreumaux, Côté, and Leconte (2018),Wild, Reed, Loucks, Mallen- Cooper, and Jensen …”