Research Article
Public Project Portfolio Optimization under a Participatory Paradigm
PROCEDURE NSGA-II (, Number_of_Generations) | Initialize Population | Generate random population with size | Evaluate objective values | Assign rank (level) based on Pareto dominance | Generate Child Population with size | Perform Binary Tournament Selection | Perform Recombination and Mutation | FOR to Number_of_Generations DO | Assign | FOR each parent and child in DO | Assign rank (level) based on Pareto dominance | Loop (inside) by adding solutions to the | next generation starting from the first front | until individual found; determine crowding | distance between points of each front | End FOR | Select points (elitist) of the lower front (with lower rank) and are outside | a crowding distance | Replace by the individual found | Generate Child Population with size | Perform Binary Tournament Selection | Perform Recombination and Mutation | End FOR | End PROCEDURE |
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