Genetic Algorithms Plus Data Structures Equals Evolution Programs
Genetic Algorithms Plus Data Structures Equals Evolution Programs
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Some experiments in machine learning using vector evaluated genetic algorithms (artificial intelligence, optimization, adaptation, pattern recognition)
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Implementation of scatter search for multi-objective optimization: a comparative study
Computational Optimization and Applications
A two-level evolutionary approach to multi-criterion optimization of water supply systems
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
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Determination of pipe diameters is the most important problem in design of water supply networks. Several authors have focused on the methods capable of sizing the network considering uncertainty and other important aspects. This study presents an application of multiobjective decision making techniques using evolutionary algorithms to generate a series of nondominated solutions. The three objective functions considered here include investment costs, entropy system and system demand supply ratio. The determination of Pareto frontier employed the public domain library MOMHLib++ and a hybrid hydraulic simulator based on the method of Nielsen. This technique is found to be quite promising, the nondominated region being identified in a reasonably small number of iterations.