Hybridizing ant colony optimization algorithm with nonlinear programming method for effective optimal design of sewer networks-Reference-Cited by-同舟云学术

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Hybridizing ant colony optimization algorithm with nonlinear programming method for effective optimal design of sewer networks

Published:2019-01-31 Issue:4 Volume:91 Page:300-321
ISSN:1061-4303
Container-title:Water Environment Research
language:en
Short-container-title:Water Environ Res

Author:

Moeini Ramtin¹²,Afshar Mohammad Hadi³

Affiliation:

1. Department of Civil EngineeringFaculty of Civil Engineering and TransportationUniversity of Isfahan Isfahan Iran

2. School of Civil EngineeringIran University of Science and Technology Narmak, Tehran Iran

3. School of Civil Engineering and Enviro‐hydroinformatic Center of ExcellenceIran University of Science and Technology Narmak, Tehran Iran

Publisher

Wiley

Subject

Water Science and Technology,Ecological Modeling,Waste Management and Disposal,Pollution,Environmental Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/wer.1027

Reference42 articles.

1. Partially constrained ant colony optimization algorithm for the solution of constrained optimization problems: Application to storm water network design

2. A parameter free Continuous Ant Colony Optimization Algorithm for the optimal design of storm sewer networks: Constrained and unconstrained approach

3. Hydrograph-based storm sewer design optimization by genetic algorithm

4. Partially and Fully Constrained Ant Algorithms for the Optimal Solution of Large Scale Reservoir Operation Problems

5. Application of cellular automata to sewer network optimization problems

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3. Wastewater reuse and energy saving require a more decentralized urban wastewater system? Evidence from multi-objective optimal design at the city scale;Water Research;2023-05

4. Application of metaheuristic algorithms in optimal design of sewer collection systems;Comprehensive Metaheuristics;2023

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