Using a Genetic Algorithm with a Mathematical Programming Solver to Optimize a Real Water Distribution System


Figure 5. Representation of an individual from the FRM network



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Using a Genetic Algorithm with a Mathematical Prog

Figure 5. Representation of an individual from the FRM network. 

Feasible  initial population. The evaluation of the population is critical because it determines 

whether an individual has the appropriate characteristics to be part of the population. The feasibility 

of each individual is determined with respect to the constraint satisfaction model. The model is 

evaluated by using EPANET solver to verify compliance with the law of conservation of mass at each 

node, the law of conservation of energy in each circuit, and the necessary pressures at each node for 

the water distribution system to function correctly. For the FRM network, a feasible solution is 

considered if each node has a minimum pressure of 10 mca and a maximum pressure of 60 mca. 

The crossover operator consists of exchanging the characteristics of two parents to generate two 

offspring. In this work, a new crossover operator is proposed called genetic interchange between 

individuals (GIBI). Figure 6 presents an example of the behavior of the GIBI operator. For the valve 

chromosome, a valve position is chosen randomly. The crossing operation was carried out in the 

operation configuration through the ‘valve setting’ attribute. The attribute ‘status’ keeps its original 

value due to valves not moving to another pipe and they are also not removed from the pipes. 

 


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