Genetic Operators and Constraint Handling for Pipe Network Optimization
Selected Papers from AISB Workshop on Evolutionary Computing
A discrete version of particle swarm optimization for flowshop scheduling problems
Computers and Operations Research
Particle swarm optimization-based algorithms for TSP and generalized TSP
Information Processing Letters
Design optimization of wastewater collection networks by PSO
Computers & Mathematics with Applications
An application of swarm optimization to nonlinear programming
Computers & Mathematics with Applications
Parametric study for an ant algorithm applied to water distribution system optimization
IEEE Transactions on Evolutionary Computation
Mathematical models and methods in the water industry
Mathematical and Computer Modelling: An International Journal
Design optimization of wastewater collection networks by PSO
Computers & Mathematics with Applications
Optimization in water systems: a PSO approach
Proceedings of the 2008 Spring simulation multiconference
Expert Systems with Applications: An International Journal
Engineering Applications of Artificial Intelligence
A metaheuristic approach to hydropower reservoir optimization based on honey bee mating algorithm
MMACTEE'10 Proceedings of the 12th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering
Tuning metaheuristics: A data mining based approach for particle swarm optimization
Expert Systems with Applications: An International Journal
Identification of surgical practice patterns using evolutionary cluster analysis
Mathematical and Computer Modelling: An International Journal
Information Sciences: an International Journal
Integrating the artificial bee colony and bees algorithm to face constrained optimization problems
Information Sciences: an International Journal
Computers and Operations Research
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In the past decade, evolutionary methods have been used by various researchers to tackle optimal design problems for water supply systems (WSS). Particle Swarm Optimization (PSO) is one of these evolutionary algorithms which, in spite of the fact that it has primarily been developed for the solution of optimization problems with continuous variables, has been successfully adapted in other contexts to problems with discrete variables. In this work we have applied one of the variants of this algorithm to two case studies: the Hanoi water distribution network and the New York City water supply tunnel system. Both cases occur frequently in the related literature and provide two standard networks for benchmarking studies. This allows us to present a detailed comparison of our new results with those previously obtained by other authors.