A multiobjective approach is used here to optimize design and operation of the C-Town pipe network, searching for trade-off solutions between (1) installation cost, (2) operational cost, and (3) cost of the pressure-reducing valves. Due to the large number of decisional variables and to the complexity of the constraints considered, the optimization problem was tackled in five steps: (1) identification of some feasible (on the basis of the many constraints) first attempt solutions; (2) application of a multiobjective genetic algorithm to the 2D optimization problem with objective functions 1 and 2, in order to obtain optimal trade-off solutions between the installation cost and operational cost, without considering the installation of pressure-reducing valves; (3) application of the multiobjective genetic algorithm to the optimization problem with objective functions 2 and 3 for each of the solution selected at the end of Step 2, in order to assess how the operational cost can decrease thanks to the installation and operation of pressure-reducing valves; (4) derivation of the 3D Pareto surface by grouping the solutions found at the end of Steps (2) and (3). A solution was extracted from the 3D Pareto surface of optimal solutions following some specific criteria. This solution was then further refined (Step 5) in order to allow for variable settings of the pressure-reducing valves installed and to make it compliant with the battle guidelines concerning leakage modeling.

Multistep Approach for Optimizing Design and Operation of the C-Town Pipe Network Model

CREACO, ENRICO FORTUNATO;
2016-01-01

Abstract

A multiobjective approach is used here to optimize design and operation of the C-Town pipe network, searching for trade-off solutions between (1) installation cost, (2) operational cost, and (3) cost of the pressure-reducing valves. Due to the large number of decisional variables and to the complexity of the constraints considered, the optimization problem was tackled in five steps: (1) identification of some feasible (on the basis of the many constraints) first attempt solutions; (2) application of a multiobjective genetic algorithm to the 2D optimization problem with objective functions 1 and 2, in order to obtain optimal trade-off solutions between the installation cost and operational cost, without considering the installation of pressure-reducing valves; (3) application of the multiobjective genetic algorithm to the optimization problem with objective functions 2 and 3 for each of the solution selected at the end of Step 2, in order to assess how the operational cost can decrease thanks to the installation and operation of pressure-reducing valves; (4) derivation of the 3D Pareto surface by grouping the solutions found at the end of Steps (2) and (3). A solution was extracted from the 3D Pareto surface of optimal solutions following some specific criteria. This solution was then further refined (Step 5) in order to allow for variable settings of the pressure-reducing valves installed and to make it compliant with the battle guidelines concerning leakage modeling.
2016
Civil Engineering covers engineering-based resources in the subfields of structural engineering, geotechnics, earthquake engineering, ocean engineering, water resources and supply, naval engineering, marine engineering, transportation engineering, and municipal engineering. Topics covered include the planning, design, construction, and maintenance of fixed structures and ground facilities for industry, occupancy, transportation, use and control of water, and harbor facilities.
Esperti anonimi
Inglese
Internazionale
ELETTRONICO
142
5
C4015005
Optimal design; Leakage; Multiobjective
no
3
info:eu-repo/semantics/article
262
Creaco, ENRICO FORTUNATO; Alvisi, Stefano; Franchini, Marco
1 Contributo su Rivista::1.1 Articolo in rivista
none
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1144782
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 14
  • ???jsp.display-item.citation.isi??? 13
social impact