Open Access
SPEA2: Improving the Strength Pareto Evolutionary Algorithm For Multiobjective Optimization
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The article was published on 2002-01-01 and is currently open access. It has received 1972 citations till now. The article focuses on the topics: Pareto principle & Multi-objective optimization.read more
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Journal ArticleDOI
Cost versus life cycle assessment-based environmental impact optimization of drinking water production plants
Florin Capitanescu,Sameer Rege,Antonino Marvuglia,Enrico Benetto,Aras Ahmadi,T. Navarrete Gutiérrez,Ligia Tiruta-Barna +6 more
TL;DR: The results of optimization reveal that good reduction in both operating cost and environmental impact of the DWPP can be obtained, and NSGA-II outperforms the other competing algorithms while MOEA/D and DE perform unexpectedly poorly.
Proceedings ArticleDOI
An efficient multi-objective evolutionary algorithm with steady-state replacement model
Dipti Srinivasan,L. Rachmawati +1 more
TL;DR: A Multi-objective Evolutionary Algorithm which avoids Pareto-ranking altogether by employing the transitivity of the domination relation is proposed, which performs favorably compared to the popular NSGA-II in terms of convergence as well as diversity of the Pare to-set approximation, and is computationally more efficient.
DissertationDOI
Cost efficient provisioning of mass mobile multimedia services in hybrid cellular and broadcasting systems
TL;DR: In this paper, a tesis doctoral aborda el problema de provision eficiente de servicios multimedia masivos a dispositivos moviles and portables utilizando the infraestructura of radiodifusion and celular existente.
Journal ArticleDOI
A provably convergent heuristic for stochastic bicriteria integer programming
TL;DR: A strict mathematical result is shown that ensures, under rather mild conditions, convergence of the current solution set to the set of Pareto-optimal solutions of bicriteria combinatorial optimization (CO) problems under uncertainty.
Journal ArticleDOI
Optimization of Allelic Combinations Controlling Parameters of a Peach Quality Model.
TL;DR: This study compared the spaces of parameters obtained with different tactics and the phenotype of the individuals resulting from random simulations and optimization in these spaces and compared a current approach based on the optimization of the values of the parameters with a more evolved way to proceed which consists in the direct optimized of the alleles controlling the parameters.