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A novel tournament selection based on multilayer cultural characteristics in gene-culture coevolutionary multitasking

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Abstract

Recently, gene-culture coevolutionary multitasking, i.e., the multifactorial evolutionary algorithm (MFEA and MFEA-II), has become increasingly popular in the area of evolutionary computation. One of the most fascinating aspects of the MFEA is that it can obtain better optimization performance by exploiting underlying complementarities and/or commonalities between different tasks synchronously. In this area, tournament selection is an important ingredient in the nondominated sorting genetic algorithm II (NSGA-II) not only for a single task but also in multitasking. When it is used in the NSGA-II, it mainly concerns individual selection for a single task. However, the selection mechanism has to be reformulated in evolutionary multitasking with different cultural characteristics. Unfortunately, until now, there has been no relevant research discussing tournament selection mechanisms in gene-culture coevolutionary multitasking. Accordingly, to clarify its selection mechanism by fully considering the cultural characteristics built into multitasking, in this paper, a novel tournament selection method based on multilayer cultural characteristics in evolutionary multitasking is proposed. In the presented method, the concept of overall rank (OR) representing a comprehensive cultural indicator is given based on the rank of the Pareto front (PF) and crowding distance. Then, the each task, PF and OR of every individual are defined as the multilayer cultural characteristics that determine the selection order. Finally, the new selection mechanism is stated clearly based on the three proposed binary tournament selection methods. The efficacy of the developed mechanism is demonstrated through testing on several benchmark functions as well as aluminum electrolysis process design in evolutionary multitasking.

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Abbreviations

OR:

Overall rank

PF:

Pareto front

BTS:

Binary tournament selection

HV:

Hypervolume

MO-MFEA:

Multi-objective multifactorial evolutionary algorithm

MFEA:

Multifactorial evolutionary algorithm

CD:

Crowding Distance

IGD:

Inverted generational distance

RMP:

Random mating probability

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Acknowledgements

We thank Prof. Yew-soon Ong for his inspiring discussion and constructive comments about the work when Lizhong Yao is a visiting scholar in the Data Science and Artificial Intelligence Research Centre (DSAIR) and the School of Computer Science and Engineering at Nanyang Technological University, Singapore. This work is also supported by the National Natural Science Foundation of China (Nos. 51805059 and 51875371), Chongqing Research Program of Basic Research and Frontier Technology under Grant (cstc2018jcyjAX0350), Special Project of Technological Innovation and Application Development in Chongqing (No.cstc2019jscx-msxmX0054) and in part by the China Scholarship Council under Grant 201802075004.

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Authors and Affiliations

  1. School of Electrical Engineering, Chongqing University of Science and Technology, Chongqing, 401331, China

    Lizhong Yao, Jun Yi, Taifu Li & Dedong Tang

  2. School of Mechanical Engineering, Sichuan University, Chengdu, 610065, China

    Lizhong Yao & Wei Long

  3. College of Information and Communication, National University of Defense Technology, Xi’an, China

    Qingzheng Xu

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  1. Lizhong Yao
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  2. Wei Long
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  3. Jun Yi
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  4. Taifu Li
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  5. Dedong Tang
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  6. Qingzheng Xu
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Correspondence to Lizhong Yao.

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Yao, L., Long, W., Yi, J. et al. A novel tournament selection based on multilayer cultural characteristics in gene-culture coevolutionary multitasking. Soft Comput 25, 9529–9543 (2021). https://doi.org/10.1007/s00500-021-05876-1

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