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Article
Publication date: 7 August 2019

Zhengrong Jiang, Quanpan Lin, Kairong Shi and Wenzhi Pan

The purpose of this paper is to propose a new hybrid algorithm, named improved plant growth simulation algorithm and particle swarm optimization hybrid algorithm (PGSA–PSO hybrid…

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Abstract

Purpose

The purpose of this paper is to propose a new hybrid algorithm, named improved plant growth simulation algorithm and particle swarm optimization hybrid algorithm (PGSA–PSO hybrid algorithm), for solving structural optimization problems.

Design/methodology/approach

To further enhance the optimization efficiency and precision of this algorithm, the optimization solution process of PGSA–PSO comprises two steps. First, an excellent initial growth point is selected by PSO. Then, the global optimal solution can be obtained quickly by PGSA and its improved strategy called growth space adjustment strategy. A typical mathematical example is provided to verify the capacity of the new hybrid algorithm to effectively improve the global search capability and search efficiency of PGSA. Moreover, PGSA–PSO is applied to the optimization design of a suspended dome structure.

Findings

Through typical mathematical example, the improved strategy can improve the optimization efficiency of PGSA considerably, and an initial growth point that falls near the global optimal solution can be obtained. Through the optimization of the pre-stress of a suspended dome structure, compared with other methods, the hybrid algorithm is effective and feasible in structural optimization.

Originality/value

Through the examples of suspended dome structure, it shows that the optimization efficiency and precision of PGSA–PSO are better than those of other algorithms and methods. PGSA–PSO is effective and feasible in structural optimization problems such as pre-stress optimization, size optimization, shape optimization and even topology optimization.

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Article
Publication date: 9 May 2018

Wenzhi Zheng, Yenchun Jim Wu and Yue Lv

The purpose of this paper is to analyze the relationship between researchers’ social media (SM) behavior and their academic performance.

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Abstract

Purpose

The purpose of this paper is to analyze the relationship between researchers’ social media (SM) behavior and their academic performance.

Design/methodology/approach

A sample of 362 researchers was recruited from the colleges of management of 52 Chinese universities. A factor analysis of eight indices retrieved from the 362 data items was conducted. A total of 24 Chinese researchers were interviewed and given a robust test.

Findings

The results indicate that Chinese general social media (GSM) is insufficient to support academic research and it is difficult for scholars to enhance the visibility of their academic performance using GSM platforms, which can actually induce addiction. University resources, management systems, and working environment affect how scholars apply SM.

Research limitations/implications

The authors examined the researchers’ SM behavior by giving them a questionnaire and interview; however, this approach proved inadequate. The academic performance of researchers is affected by numerous factors, but the authors only considered SM behavior.

Practical implications

It is suggested that universities apply academic social media (ASM) indicators to measure researchers’ contributions so that they self-regulate their SM usage attitudes. Also, universities should also promote ASM platforms.

Originality/value

This study analyzed scholars’ GSM usage and academic performance, and the moderating effect of university level on the relationship between need for competence and relatedness and need for autonomy. This comprehensive analysis contributes to the scholarly SM usage literature.

Details

Library Hi Tech, vol. 37 no. 1
Type: Research Article
ISSN: 0737-8831

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