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Table of Content

Bio-inspired Optimization in Engineering and Sciences

Submission Deadline: 01 February 2024 (closed)

Guest Editors

Prof. Dr. Yudong Zhang, University of Leicester, UK
Prof. Dr. Huiling Chen, Wenzhou University, China

Summary

Bio-inspired optimization algorithms are a set of optimization algorithms inspired by natural phenomena, such as evolutionary processes, social behavior, and swarm intelligence. These algorithms attempt to simulate these processes to solve optimization problems. Classical bio-inspired algorithms include genetic algorithm, ant colony optimization, artificial bee colony, particle swarm optimization, firefly algorithm, Japanese tree frog algorithm, Harris hawks optimizer, etc.

 

Bio-inspired optimization algorithms can be applied to engineering and sciences in several ways, such as biomarker extraction, image segmentation, disease classification, lesion localization, treatment recommendation, etc.

 

This special issue plans to report the recent advances in bio-inspired optimization in Engineering and Sciences. The ultimate goal of this special issue is to promote research and development of bio-inspired optimization theories and their applications in engineering and sciences by publishing high-quality research articles and surveys in this rapidly growing interdisciplinary field.

 

Topics of interest should include, but not be limited to

 

• Genetic algorithm

• Particle swarm optimization

• Ant colony optimization

• Artificial bee colony

• Firefly algorithm

• Japanese tree frog algorithm

• Harris hawks optimization

• Slime mould algorithm

• Grey wolf optimization

• Sparrow search algorithm

• Whale optimization algorithm

• Bio-inspired algorithms for multi-objective optimization

• Hybrid bio-inspired algorithms

• Parallel and distributed bio-inspired algorithms

• Brain-inspired cognitive architectures



Published Papers


  • Open Access

    ARTICLE

    Prediction of Ground Vibration Induced by Rock Blasting Based on Optimized Support Vector Regression Models

    Yifan Huang, Zikang Zhou, Mingyu Li, Xuedong Luo
    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3147-3165, 2024, DOI:10.32604/cmes.2024.045947
    (This article belongs to this Special Issue: Bio-inspired Optimization in Engineering and Sciences)
    Abstract Accurately estimating blasting vibration during rock blasting is the foundation of blasting vibration management. In this study, Tuna Swarm Optimization (TSO), Whale Optimization Algorithm (WOA), and Cuckoo Search (CS) were used to optimize two hyperparameters in support vector regression (SVR). Based on these methods, three hybrid models to predict peak particle velocity (PPV) for bench blasting were developed. Eighty-eight samples were collected to establish the PPV database, eight initial blasting parameters were chosen as input parameters for the prediction model, and the PPV was the output parameter. As predictive performance evaluation indicators, the coefficient of determination (R2), root mean square… More >

  • Open Access

    ARTICLE

    Crashworthiness Design and Multi-Objective Optimization of Bionic Thin-Walled Hybrid Tube Structures

    Pingfan Li, Jiumei Xiao
    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 999-1016, 2024, DOI:10.32604/cmes.2023.044059
    (This article belongs to this Special Issue: Bio-inspired Optimization in Engineering and Sciences)
    Abstract Thin-walled structures are widely used in cars due to their lightweight construction and energy-absorbing properties. However, issues such as high initial stress and low energy-absorbing efficiency arise. This study proposes a novel energy-absorbing structure in which a straight tube is combined with a conical tube and a bamboo-inspired bulkhead structure is introduced. This configuration allows the conical tube to flip outward first and then fold together with the straight tube. This deformation mode absorbs more energy and less peak force than the conical tube sinking and flipping inward. Through finite element numerical simulation, the specific energy absorption capacity of the… More >

  • Open Access

    EDITORIAL

    Bio-Inspired Optimization in Engineering and Sciences

    Yudong Zhang, Huiling Chen
    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1065-1067, 2023, DOI:10.32604/cmes.2023.029710
    (This article belongs to this Special Issue: Bio-inspired Optimization in Engineering and Sciences)
    Abstract This article has no abstract. More >

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