Use this URL to cite or link to this record in EThOS:
Title: Many-objective evolutionary algorithms and applications to water resources engineering
Author: di Pierro, Francesco
ISNI:       0000 0001 3423 3900
Awarding Body: University of Exeter
Current Institution: University of Exeter
Date of Award: 2006
Availability of Full Text:
Access from EThOS:
Over the last ten years, Multi-Objective Evolutionary Algorithms (MOEAs) have undergone tremendous development and have been successfully applied in various fields to solve complex problems that were formulated typically with two or three objectives. However, an increasingly expanding basis of our knowledge of natural processes and engineering requirements, and the need of taking into account sustainability indicators in order to compensate for the socio-environmental damage caused by the human activity, has increasingly led to formulation of the real world optimisation problems requiring a large number of management criteria.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available