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Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms
[chapter]
2009
Lecture Notes in Computer Science
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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
2019
Complex & Intelligent Systems
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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]
2017
Heuristics and Hyper-Heuristics - Principles and Applications
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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
2015
Applied Soft Computing
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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
2019
European Journal of Operational Research
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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]
2016
Lecture Notes in Computer Science
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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
2018
Water
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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
2018
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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