Chance-constrained multi-objective programming for optimal multi-layer aquifer remediation design

Groundwater remediation works are expensive, complex in nature, and generally involve uncertain design parameters and multiple conflicting objectives. Reduction in remediation cost is, normally, the primary objective of optimal remediation designs. Remediation time has significant influence on remed...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Engineering optimization Jg. 43; H. 4; S. 417 - 432
Hauptverfasser: Singh, Thangjam Somch, Chakrabarty, Dibakar
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Abingdon Taylor & Francis 01.04.2011
Taylor & Francis Ltd
Schlagworte:
Aquifers
Cost engineering
Decision making
evolutionary algorithms
Exploration
Groundwater
Groundwater remediation
Mathematical models
Mathematical programming
multi-objective optimization
Multilayers
numerical models
Optimization
Optimization algorithms
Programming
remedial action
Remediation
Uncertainty
ISSN:0305-215X, 1029-0273
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Groundwater remediation works are expensive, complex in nature, and generally involve uncertain design parameters and multiple conflicting objectives. Reduction in remediation cost is, normally, the primary objective of optimal remediation designs. Remediation time has significant influence on remediation cost. The main contributions of this study are: development of a chance-constrained multi-objective programming (CCMOP) model, exploration of the significance of flexible remediation time on optimal remediation designs, and exploration of some basic characteristics of multi-objective optimization algorithms. The developed methodology excludes inferior yet optimal solutions from the set of possible solutions, identifies the ranges in which non-inferior solutions lie, and prevents one from making inferior decisions. It provides insightful information about the problem and simplifies the decision making process considerably. The results suggest that by avoiding the use of faulty remediation times, highly significant amounts of remediation cost could be saved. The CCMOP is an effective uncertainty and reliability prediction technique.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:0305-215X
1029-0273
DOI:10.1080/0305215X.2010.491548