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Extending the GA-EDA Hybrid Algorithm to Study Diversification and Intensification in GAs and EDAs [chapter]

V. Robles, J. M. Peña, M. S. Pérez, P. Herrero, O. Cubo
2005 Lecture Notes in Computer Science  
This approach had allowed us to make an study of the balance of diversification (exploration) and intensification (exploitation) in Genetic Algorithms and Estimation of Distribution Algorithms.  ...  The use of parallel EDAs in a island model [18] is an of this. The hybrid algorithm GA-EDA, can be classified as cooperative search in Blum and Roli's taxonomy.  ...  Besides, diversification and intensification of both GA and EDA algorithms have been analyzed.  ... 
doi:10.1007/11552253_31 fatcat:2rsm5yopirgczdjzkgde5jwkdy

Guidelines for developing effective Estimation of Distribution Algorithms in solving single machine scheduling problems

Shih-Hsin Chen, Min-Chih Chen, Pei-Chann Chang, Qingfu Zhang, Yuh-Min Chen
2010 Expert systems with applications  
These guidelines aim at balancing intensification and diversification in EDAs. Most EDAs are able to maintain some important linkages among variables.  ...  The major ideas are to increase the population diversity gradually and by hybridizing EDAs with other meta-heuristics.  ...  The solution quality of these algorithms can be further enhanced by implementing the searching strategy of intensification using the EDAs and diversification via GAs.  ... 
doi:10.1016/j.eswa.2010.02.073 fatcat:k2hx7pbvefcahhbmu4z3s4f6m4

Cyber-EDA: Estimation of Distribution Algorithms with Adaptive Memory Programming

Peng-Yeng Yin, Hsi-Li Wu
2013 Mathematical Problems in Engineering  
In contrast to classic evolutionary algorithms (EAs), EDA framework is flexible and is able to handle inter variable dependence, which usually imposes difficulties on classic EAs.  ...  The estimation of distribution algorithm (EDA) aims to explicitly model the probability distribution of the quality solutions to the underlying problem.  ...  [10] hybridized PSO with tabu search to implement intensification and diversification searches more effectively.  ... 
doi:10.1155/2013/132697 fatcat:dsa4ru7qa5aq7fxawd6vu5lozy

An estimation of distribution algorithm for lot-streaming flow shop problems with setup times

Quan-Ke Pan, Rubén Ruiz
2012 Omega : The International Journal of Management Science  
In the proposed EDA, an efficient initialization scheme based on the NEH heuristic is presented to construct an initial population with a certain level of quality and diversity.  ...  The results show that the proposed EDA is very effective in comparison after comprehensive computational and statistical analyses.  ...  In this research, we extend it to handle the studied problem, and obtain two heuristics, referred to as NEH1 and NEH2, respectively.  ... 
doi:10.1016/ fatcat:tl62yhgqmzc5ffomyev4tufh7e

A Hybrid GA-SQP Algorithm for Analog Circuits Sizing

Firas Yengui, Lioua Labrak, Felipe Frantz, Renaud Daviot, Nacer Abouchi, Ian O'Connor
2012 Circuits and Systems  
This study presents a hybrid algorithm obtained by combining a genetic algorithm (GA) with successive quadratic sequential programming (SQP), namely GA-SQP.  ...  The outcome is very encouraging and suggests that the hybrid proposed method is very efficient in solving analog design problems.  ...  The GA acts over a population of potential solutions, applying intensification (crossover) and diversification (mutation) operators to explore the problem space.  ... 
doi:10.4236/cs.2012.32019 fatcat:znol6t5f4fddpmqsjqvoisjese

Local search methods for the flowshop scheduling problem with flowtime minimization

Quan-Ke Pan, Rubén Ruiz
2012 European Journal of Operational Research  
Total flowtime minimization of a flowshop has been actively studied and many effective algorithms have been proposed in the last few years.  ...  However, these improvements many times come at the cost of sophisticated algorithms. Complex methods hinder potential applications and are difficult to extend to small problem variations.  ...  Diversification and intensification are two key issues in the optimization process of population-based methods.  ... 
doi:10.1016/j.ejor.2012.04.034 fatcat:qjspgxtakngbtbmwgnbxxxk5oy

Meta-heuristics for manufacturing scheduling and logistics problems

Ching-Jong Liao, Mitsuo Gen, Manoj Kumar Tiwari, Pei-Chann Chang
2013 International Journal of Production Economics  
In addition, the authors employed an extended priority-based encoding method, combining a local search (LS) technique and a new fuzzy logic control (FLC) to enhance the search ability of the hybrid evolutionary  ...  In this approach, the authors carried out two separate evolution simultaneously; population 1 employed for diversification while population 2 using for evolution intensification.  ... 
doi:10.1016/j.ijpe.2012.09.004 fatcat:ri2ogbsa6rbqpi2s3vnkenhhz4

R-EVO: A Reactive Evolutionary Algorithm for the Maximum Clique Problem

Mauro Brunato, Roberto Battiti
2011 IEEE Transactions on Evolutionary Computation  
In the framework of estimation-of-distribution algorithms (EDA), guided mutation uses a model distribution to generate the offspring by combining the local information of solutions found so far with global  ...  The novel reactive and evolutionary algorithm (R-EVO) proposed in this paper starts from the same evolutionary framework but considers more complex individuals, which modify tentative solutions by local  ...  ACKNOWLEDGMENT The authors would like to thank Q. Zhang for sending the original software used in [13] and to acknowledge support by F.  ... 
doi:10.1109/tevc.2010.2043363 fatcat:vupybo7k2nabng42dcu33tnnku

Simulated Annealing with Exploratory Sensing for Global Optimization

Majid Almarashi, Wael Deabes, Hesham H. Amin, Abdel-Rahman Hedar
2020 Algorithms  
In this work, a methodology of two phases using an automatic diversification and intensification based on memory and sensing tools is proposed.  ...  Unlike memory-based search algorithms such as the tabu search, the search in simulated annealing is dependent on the choice of the initial temperature to explore the search space, which has little indications  ...  In the past four decades, many applications and studies have applied Metaheuristics algorithms. tabu search (TS) [1] , simulated annealing (SA) [2] , genetic algorithms (GAs) [3] , and other plentiful  ... 
doi:10.3390/a13090230 fatcat:nsgeot6eubh4pjuwee2jjfsncu

An Overview on the Latest Nature-Inspired and Metaheuristics-Based Image Registration Algorithms

J. Santamaría, M.L. Rivero-Cejudo, M.A. Martos-Fernández, F. Roca
2020 Applied Sciences  
Finally, our research has shown that the field of nature-inspired and metaheuristic algorithms has increased its interest in the last decade to address the IR problem, and it has been highlighted that  ...  IR has been applied to a high number of real-world scenarios ranging from remote sensing to medical imaging, artificial vision, and computer-aided design.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app10061928 fatcat:acj6tp7q5navpdhgmif6yep2fu

Differential Evolution with an Evolution Path: A DEEP Evolutionary Algorithm

Yuan-Long Li, Zhi-Hui Zhan, Yue-Jiao Gong, Wei-Neng Chen, Jun Zhang, Yun Li
2015 IEEE Transactions on Cybernetics  
It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output.  ...  The Strathprints institutional repository ( is a digital archive of University of Strathclyde research outputs.  ...  Other relevant studies have focused on using a DM as a base algorithm, such as the combinations of DE and EDA [17] , [19] , PSO and EDA [15] , and DE and CMA-ES [21] .  ... 
doi:10.1109/tcyb.2014.2360752 pmid:25314717 fatcat:c2amuegc2faajm7oqfx3gu6dum

Classifier ensemble reduction using a modified firefly algorithm: An empirical evaluation

Li Zhang, Worawut Srisukkham, Siew Chin Neoh, Chee Peng Lim, Diptangshu Pandit
2018 Expert systems with applications  
The extended model also employed an adaptive attractiveness coefficient to achieve a higher intensification capability.  ...  Many meta-heuristic or learning/search mechanisms, such as GA, PSO, DE, Ant-Lion Optimization (ALO), memetic algorithm, cellular learning automata and neural networks, have been hybridized with FA to increase  ...  Other adaptive parameter tuning strategies and hybrid evading actions will also be studied to further improve the robustness of the proposed algorithm.  ... 
doi:10.1016/j.eswa.2017.10.001 fatcat:o3t6fgq5yng5hcfhz33lu7jie4

The development and application of metaheuristics for problems in graph theory: a computational study

Sergio Consoli
2011 4OR  
For this purpose, an algorithm based on Ant Colony Optimization (ACO) is currently under study in order to try to obtain a larger diversification capability by extending the current greedy MVCA local search  ...  As in Group 1, PILOT and MGA obtain worse solutions and their defects of excessive diversification and poor intensification for MGA and, conversely, of excessive intensification and poor diversification  ... 
doi:10.1007/s10288-011-0187-3 fatcat:uybenvacn5ebvfaklscfbt52km

Heuristic and Metaheuristic Methods for the Unrelated Machines Scheduling Problem: A Survey [article]

Marko Đurasević, Domagoj Jakobović
2021 arXiv   pre-print
However, no study has until now tried to systematise the research in which heuristic methods are applied for the UPMSP.  ...  The goal of this study is to provide an extensive literature review on the application of heuristic and metaheuristic methods for solving the UPMSP.  ...  The authors use TS with different strategies that focus either on intensification or diversification of solutions during optimisation.  ... 
arXiv:2107.13106v1 fatcat:e3eijbxklbeulefyv3t5kcu2im

The 0/1 Multidimensional Knapsack Problem and Its Variants: A Survey of Practical Models and Heuristic Approaches

Soukaina Laabadi, Mohamed Naimi, Hassan El Amri, Boujemâa Achchab
2018 American Journal of Operations Research  
A study of the Stony Brook University Algorithm Repository [2], carried out in 1998, stipulates that the knapsack problem (especially the MKP) was the 18th most popular and the 4th most needed problem  ...  Even though the 0/1 MKP is well studied in the literature, we can just find a little number of recent review papers on this problem.  ...  Conflicts of Interest The authors declare no conflicts of interest regarding the publication of this paper.  ... 
doi:10.4236/ajor.2018.85023 fatcat:3gj2dpb7preahdrpbtveuijgli
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