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Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms [chapter]

Carlos Segura, Alejandro Cervantes, Antonio J. Nebro, María Dolores Jaraíz-Simón, Eduardo Segredo, Sandra García, Francisco Luna, Juan Antonio Gómez-Pulido, Gara Miranda, Cristóbal Luque, Enrique Alba, Miguel Ángel Vega-Rodríguez (+2 others)
2009 Lecture Notes in Computer Science  
The cooperation of a team of multi-objective evolutionary algorithms has been performed with a novel optimization model.  ...  Such model is a hybrid parallel algorithm that combines a parallel islandbased scheme with a hyperheuristic approach.  ...  The model is based on the hybridization of parallel islandbased evolutionary algorithms and hyperheuristics.  ... 
doi:10.1007/978-3-642-01020-0_26 fatcat:ijmtk4ytanbvparxad2ez3qhxq

Evolutionary multiobjective optimization: open research areas and some challenges lying ahead

Carlos A. Coello Coello, Silvia González Brambila, Josué Figueroa Gamboa, Ma Guadalupe Castillo Tapia, Raquel Hernández Gómez
2019 Complex & Intelligent Systems  
Evolutionary multiobjective optimization has been a research area since the mid-1980s, and has experienced a very significant activity in the last 20 years.  ...  The main aim of this paper is to motivate researchers and students to develop research in these areas, as this will contribute to maintaining this discipline active during the next few years.  ...  , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s40747-019-0113-4 fatcat:m5llfto6gzh4doap6gr3fmfwje

Multi‐Objective Hyper‐Heuristics [chapter]

Mashael Suliaman Maashi
2017 Heuristics and Hyper-Heuristics - Principles and Applications  
Some design issues related to the development of hyper-heuristic framework for multi-objective optimization are discussed.  ...  Work on hyper-heuristics for multi-objective optimization remains limited.  ...  Nevertheless, upcoming efforts are still necessary in advancing the approach. In Ref. [36] , a hypervolume-based hyper-heuristic for a dynamic-mapped multi-objective island-based model is proposed.  ... 
doi:10.5772/intechopen.69222 fatcat:lofar2izwvabpcedgnss6yo5q4

Choice function based hyper-heuristics for multi-objective optimization

Mashael Maashi, Graham Kendall, Ender Özcan
2015 Applied Soft Computing  
methods for multi-objective optimization.  ...  A well known hypervolume metric is integrated into the move acceptance methods to enable the approaches to deal with multi-objective problems.  ...  The authors thank the University of Tabuk and Ministry of Higher Education in Saudi Arabia for funding this work.  ... 
doi:10.1016/j.asoc.2014.12.012 fatcat:ufuhnsqtm5ce3dfnniaacxzlzy

Recent Advances in Selection Hyper-heuristics

John H. Drake, Ahmed Kheiri, Ender Özcan, Edmund K. Burke
2019 European Journal of Operational Research  
Hyper-heuristics have emerged as a way to raise the level of generality of search techniques for computational search problems.  ...  The current state-of-the-art in hyper-heuristic research comprises a set of methods that are broadly concerned with intelligently selecting or generating a suitable heuristic for a given situation.  ...  Acknowledgments This work has been partially funded by the DAASE project, EPSRC programme grant EP/J017515/1 and the OR-MASTER project, EPSRC programme grant EP/M020258/1 .  ... 
doi:10.1016/j.ejor.2019.07.073 fatcat:ojfs237tynhxbgtyiho6dagapi

Reducing Efficiency of Connectivity-Splitting Attack on Newscast via Limited Gossip [chapter]

Jakub Muszyński, Sébastien Varrette, Pascal Bouvry
2016 Lecture Notes in Computer Science  
Although static multi-objective evolutionary algorithms have been adapted for solving the DMOPs in the literature, some of those extensions may have high running time and may be inefficient for the given  ...  Algorithms for Evolutionary Multi-objective Optimization of Invariant-Noise Problems Florian Siegmund, Amos H.C.  ... 
doi:10.1007/978-3-319-31204-0_20 fatcat:27rnwllk75cv5kncys2u7utreq

Lost in Optimisation of Water Distribution Systems? A Literature Review of System Design

Helena Mala-Jetmarova, Nargiz Sultanova, Dragan Savic
2018 Water  
Optimisation of WDS design has also progressed from a cost-driven single-objective framework to multi-objective models, when various objectives that continually gain importance (e.g., environmental objectives  ...  To generate multi-objective optimal solutions, those studies use mainly metaheuristics or hyperheuristics, such as structured messy GA (SMGA) [63], NSGA-II [95], non-dominated sorting evolution strategy  ...  time and improve the quality of solutions obtained. • Two parallel models, global and island, are used.  ... 
doi:10.3390/w10030307 fatcat:7g7cx57xpzhpzeg55lw4qeazly

Multiobjective Optimization for Space Systems Architecture: Applying and Extracting Knowledge

Nozomi Hitomi
LIST OF FIGURES 2.1 The general flow of an AOS strategy for MOEAs . . . . . . . . . . 2.2 Boxplot of HV achieved by single operator MOEAs on the WFG7 and DTLZ7 problems.  ...  Other operator selection strategies based on multi-armed bandit algorithms [32, 58, 59, 103] , choice functions [30, 69, 117] , dynamic island models [19, 170] , or Markov chain models [125] have  ...  The proposed tool encodes the extracted knowledge as evolutionary operators and uses them with an AOS to guide the remainder of the optimization process.  ... 
doi:10.7298/x4pn93wb fatcat:qzp2ni4svvdu7o65ruf3gg5qam