A novel adaptive hybrid crossover operator for multiobjective evolutionary algorithm

Zhu, Qingling; Lin, Qiuzhen; Du, Zhihua; Liang, Zhengping; Wang, Wenjun; Zhu, Zexuan; Chen, Jianyong; Huang, Pei-Zhi; Ming, Zhong

doi:10.1016/j.ins.2016.01.046

Cited by 53 publications

(19 citation statements)

References 53 publications

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“…With smartphones, many internet-based services have also shifted to mobile devices, including IMs, SNS, email, and so on. As the most widely used technology and most common electronic device in the world, it was estimated that the unique number of mobile phone subscribers would increase from 4.7 billion in 2015 to 5.6 billion by 2020, accounting to a penetration rate of 63% and 72% of the global population, respectively [27,28,29].…”

Section: Mobile Communicationmentioning

confidence: 99%

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Dynamics of information diffusion and its applications on complex networks

et al. 2016

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The ongoing rapid expansion of the Word Wide Web (WWW) greatly increases the information of effective transmission from heterogeneous individuals to various systems. Extensive research for information diffusion is introduced by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and empirical studies, unification and comparison of different theories and approaches are lacking, which impedes further advances. In this article, we review recent developments in information diffusion and discuss the major challenges. We compare and evaluate available models and algorithms to receptively investigate their physical roles and optimization designs. Potential impacts and future directions are discussed. We emphasize that information diffusion has great scientific depth and combines diverse research fields which makes it interesting for physicists as well as interdisciplinary researchers.

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Section: Mobile Communicationmentioning

confidence: 99%

“…With the Y m×1 and Φ m×(n−1) inferred from times series of nodal states, we can reconstruct all adjacent relationships between node i and other nodes by using standard solutions of CST to solve Eq. (29). Similarly, neighbors of all nodes can be uncovered, that is the full reconstruction of network can be achieved.…”

Section: Cst-based Reconstructionmentioning

confidence: 99%

Dynamics of information diffusion and its applications on complex networks

et al. 2016

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“…It is validated that a little random perturbation of can bring better effectiveness for the optimization process [17]. As a result, it is randomly generated within the range [0.…”

Section: Moea/d-dra With Lsiasmentioning

confidence: 99%

“…The simulated binary crossover (SBX) [13] and the differential operator (DE) [14] are widely adopted, and they 2 Mathematical Problems in Engineering are usually combined with the binomial crossover or the polynomial mutation, as these combinations could bring powerful search ability [15,16]. There are still some limitations for composite operators [17] and variants [18] when searching complex problems. However, more and more adaptive control strategies are considered indispensable.…”

Section: Introductionmentioning

confidence: 99%

“…In [19], best individuals are selected as donor vectors for the DE, and the parameter of every mutation vary within the range of the statistical data of each generation. Zhu et al [17] design a novel recombination operator possessing the advantages of both the DE and the SBX. Its adaptive parameter control strategy is to allocate probabilities for SBX and DE according to the search period, whereas Zhao et al [20] suggest that the different neighborhood sizes have an unavoidable influence on the search power of operators based on the framework of MOEA/D, and the experiments imply that adaptive selection of neighborhood sizes works very well.…”

Section: Introductionmentioning

confidence: 99%

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Latest Stored Information Based Adaptive Selection Strategy for Multiobjective Evolutionary Algorithm

Gao

Qing-hua

Fan

et al. 2017

Mathematical Problems in Engineering

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The adaptive operator selection (AOS) and the adaptive parameter control are widely used to enhance the search power in many multiobjective evolutionary algorithms. This paper proposes a novel adaptive selection strategy with bandits for the multiobjective evolutionary algorithm based on decomposition (MOEA/D), named latest stored information based adaptive selection (LSIAS). An improved upper confidence bound (UCB) method is adopted in the strategy, in which the operator usage rate and abandonment of extreme fitness improvement are introduced to improve the performance of UCB. The strategy uses a sliding window to store recent valuable information about operators, such as factors, probabilities, and efficiency. Four common used DE operators are chosen with the AOS, and two kinds of assist information on operator are selected to improve the operators search power. The operator information is updated with the help of LSIAS and the resulting algorithmic combination is called MOEA/D-LSIAS. Compared to some well-known MOEA/D variants, the LSIAS demonstrates the superior robustness and fast convergence for various multiobjective optimization problems. The comparative experiments also demonstrate improved search power of operators with different assist information on different problems.

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Generalized Hybrid Evolutionary Algorithm Framework with a Mutation Operator Requiring no Adaptation

Foo

Goh

Chan

et al. 2017

Lecture Notes in Computer Science

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This paper presents a generalized hybrid evolutionary optimization structure that not only combines both nondeterministic and deterministic algorithms on their individual merits and distinct advantages, but also offers behaviors of the three originating classes of evolutionary algorithms (EAs). In addition, a robust mutation operator is developed in place of the necessity of mutation adaptation, based on the mutation properties of binary-coded individuals in a genetic algorithm. The behaviour of this mutation operator is examined in full and its performance is compared with adaptive mutations. The results show that the new mutation operator outperforms adaptive mutation operators while reducing complications of extra adaptive parameters in an EA representation.

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A novel adaptive hybrid crossover operator for multiobjective evolutionary algorithm

Cited by 53 publications

References 53 publications

Dynamics of information diffusion and its applications on complex networks

Dynamics of information diffusion and its applications on complex networks

Latest Stored Information Based Adaptive Selection Strategy for Multiobjective Evolutionary Algorithm

Generalized Hybrid Evolutionary Algorithm Framework with a Mutation Operator Requiring no Adaptation

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