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Article
Publication date: 16 April 2018

Qi Zhou, Xinyu Shao, Ping Jiang, Tingli Xie, Jiexiang Hu, Leshi Shu, Longchao Cao and Zhongmei Gao

Engineering system design and optimization problems are usually multi-objective and constrained and have uncertainties in the inputs. These uncertainties might…

Abstract

Purpose

Engineering system design and optimization problems are usually multi-objective and constrained and have uncertainties in the inputs. These uncertainties might significantly degrade the overall performance of engineering systems and change the feasibility of the obtained solutions. This paper aims to propose a multi-objective robust optimization approach based on Kriging metamodel (K-MORO) to obtain the robust Pareto set under the interval uncertainty.

Design/methodology/approach

In K-MORO, the nested optimization structure is reduced into a single loop optimization structure to ease the computational burden. Considering the interpolation uncertainty from the Kriging metamodel may affect the robustness of the Pareto optima, an objective switching and sequential updating strategy is introduced in K-MORO to determine (1) whether the robust analysis or the Kriging metamodel should be used to evaluate the robustness of design alternatives, and (2) which design alternatives are selected to improve the prediction accuracy of the Kriging metamodel during the robust optimization process.

Findings

Five numerical and engineering cases are used to demonstrate the applicability of the proposed approach. The results illustrate that K-MORO is able to obtain robust Pareto frontier, while significantly reducing computational cost.

Practical implications

The proposed approach exhibits great capability for practical engineering design optimization problems that are multi-objective and constrained and have uncertainties.

Originality/value

A K-MORO approach is proposed, which can obtain the robust Pareto set under the interval uncertainty and ease the computational burden of the robust optimization process.

Details

Engineering Computations, vol. 35 no. 2
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 18 April 2017

Qi Zhou, Ping Jiang, Xinyu Shao, Hui Zhou and Jiexiang Hu

Uncertainty is inevitable in real-world engineering optimization. With an outer-inner optimization structure, most previous robust optimization (RO) approaches under…

Abstract

Purpose

Uncertainty is inevitable in real-world engineering optimization. With an outer-inner optimization structure, most previous robust optimization (RO) approaches under interval uncertainty can become computationally intractable because the inner level must perform robust evaluation for each design alternative delivered from the outer level. This paper aims to propose an on-line Kriging metamodel-assisted variable adjustment robust optimization (OLK-VARO) to ease the computational burden of previous VARO approach.

Design/methodology/approach

In OLK-VARO, Kriging metamodels are constructed for replacing robust evaluations of the design alternative delivered from the outer level, reducing the nested optimization structure of previous VARO approach into a single loop optimization structure. An on-line updating mechanism is introduced in OLK-VARO to exploit the obtained data from previous iterations.

Findings

One nonlinear numerical example and two engineering cases have been used to demonstrate the applicability and efficiency of the proposed OLK-VARO approach. Results illustrate that OLK-VARO is able to obtain comparable robust optimums as to that obtained by previous VARO, while at the same time significantly reducing computational cost.

Practical implications

The proposed approach exhibits great capability for practical engineering design optimization problems under interval uncertainty.

Originality/value

The main contribution of this paper lies in the following: an OLK-VARO approach under interval uncertainty is proposed, which can significantly ease the computational burden of previous VARO approach.

Details

Engineering Computations, vol. 34 no. 2
Type: Research Article
ISSN: 0264-4401

Keywords

Open Access
Article
Publication date: 19 July 2022

Houbin Fang, Lili Wang and Qi Zhou

The purpose of this study is to evaluate the effectiveness of one online PD in PBL. Researchers want to investigate if a five-day international online PBL training will…

Abstract

Purpose

The purpose of this study is to evaluate the effectiveness of one online PD in PBL. Researchers want to investigate if a five-day international online PBL training will prepare teachers to implement PBL in their classrooms. Secondly, the researchers aim to determine if the training provides teachers with sufficient knowledge and support to ensure successful PBL implementation.

Design/methodology/approach

Participants were given a 5-day (20 h) online PBL training created by one of the researchers with three frontline teachers. Seven trainers are divided into four groups for four groups of participants. Group A included Grade 1 and Grade 2 teachers, Group B included Grade 3 and Grade 4 teachers, Group C included Grade 5 and Grade 6 teachers, and Group D consisted of Grades 7 through 9 teachers. All the participants were given exactly the same surveys at the beginning and the end of the training.

Findings

Consistent with previous studies comparing in person and virtue PD programs, this five-day interactive PD program was effective in increasing teachers' knowledge of and ability to plan and implement PBL projects. Specifically, results showed that teachers' knowledge level of PBL shifted from a shallow understanding of what the name implies to a deeper, more comprehensive, and more concrete understanding of PBL essential concepts, its pedagogical values, specific process involved in a PBL project. In addition, the PD program increased teachers' comfort level and ability of planning and implementing PBL projects across grade levels and subject areas.

Originality/value

This research study supported the previous study results that virtual PD programs can be as effective as in person programs. Further, this is the study discovered the effectiveness of PBL training between the US and China through online format, which has not been conducted literately before. The positive results will be used to promote the online collaboration internationally in the future.

Details

Journal of Research in Innovative Teaching & Learning, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2397-7604

Keywords

Article
Publication date: 7 September 2020

Yuanqiong He, Qi Zhou, Shuojia Guo and Jie Xiong

This study aims to investigate the construal congruence of anthropomorphized brand roles and product messaging and its underlying mechanism on consumers' product attitude.

Abstract

Purpose

This study aims to investigate the construal congruence of anthropomorphized brand roles and product messaging and its underlying mechanism on consumers' product attitude.

Design/methodology/approach

Four experimental studies were conducted to test the hypotheses. Study 1 investigated the framing effect of anthropomorphized brand roles (servant vs partner) in consumers' minds. Study 2 examined the matching effect of anthropomorphized brand roles and product messaging on product attitude. 132 students were randomly assigned to a 2 (anthropomorphized roles: servant vs partner) × 2 (product messaging: higher-level construal vs lower-level construal) between-subject factorial design. Study 3 tested the mediation effect of processing fluency underlying the construal congruence mechanism. Study 4 replicated the results of study 3 and further examined the boundary conditions by introducing product innovation locus as a moderator. A total of 218 students were randomly assigned to a 2 (anthropomorphized role: servant vs partner) × 2 (product messaging: higher-level construal vs lower-level construal) × 2 (innovation locus: core innovation vs peripheral locus) between-subjects design experiment.

Findings

The results demonstrate that a construal match between product messaging and anthropomorphized brand roles –anthropomorphized “servant” with higher-level construal messaging and anthropomorphized “partner” with lower-level construal messaging – can positively influence consumers' attitude via enhanced processing fluency. Furthermore, this construal matching effect on product attitude is moderated by the innovation locus of the product.

Practical implications

This study reveals that anthropomorphized brand roles with compatible product messaging in the associated construal levels lead to more favorable product attitudes. Furthermore, the matching effect of anthropomorphized brand roles and product messaging is stronger for products with peripheral innovation than with core innovation.

Originality/value

Our study contributes to the literature in two ways. First, it provides new insights into the construal matching effect of anthropomorphized brand roles and product messaging. Second, it investigates the boundary conditions of the above-mentioned construal fit mechanism.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 33 no. 4
Type: Research Article
ISSN: 1355-5855

Keywords

Article
Publication date: 13 July 2021

Yating Li, Chi Zhou, Di Wu and Min Chen

Advances in information technology now permit the recording of massive and diverse process data, thereby making data-driven evaluations possible. This study discusses…

Abstract

Purpose

Advances in information technology now permit the recording of massive and diverse process data, thereby making data-driven evaluations possible. This study discusses whether teachers’ information literacy can be evaluated based on their online information behaviors on online learning and teaching platforms (OLTPs).

Design/methodology/approach

First, to evaluate teachers’ information literacy, the process data were combined from teachers on OLTP to describe nine third-level indicators from the richness, diversity, usefulness and timeliness analysis dimensions. Second, propensity score matching (PSM) and difference tests were used to analyze the differences between the performance groups with reduced selection bias. Third, to effectively predict the information literacy score of each teacher, four sets of input variables were used for prediction using supervised learning models.

Findings

The results show that the high-performance group performs better than the low-performance group in 6 indicators. In addition, information-based teaching and behavioral research data can best reflect the level of information literacy. In the future, greater in-depth explorations are needed with richer online information behavioral data and a more effective evaluation model to increase evaluation accuracy.

Originality/value

The evaluation based on online information behaviors has concrete application scenarios, positively correlated results and prediction interpretability. Therefore, information literacy evaluations based on behaviors have great potential and favorable prospects.

Article
Publication date: 20 June 2017

Hang Ye, Abhishek Venketeswaran, Sonjoy Das and Chi Zhou

One of the major concerns of the constrained-surface stereolithography (SLA) process is that the built-up part may break because of the force resulting from the pulling-up…

548

Abstract

Purpose

One of the major concerns of the constrained-surface stereolithography (SLA) process is that the built-up part may break because of the force resulting from the pulling-up process. This resultant force may become significant if the interface mechanism between the two contact surfaces (i.e. newly cured layer and the bottom of the resin vat) produces a strong bonding between them. The purpose of this paper is to characterize the separation process between the cured part and the resin vat by adopting an appropriate and simple mechanics-based model that can be used to probe the pulling-up process.

Design/methodology/approach

In this paper, the time-histories of the pulling-up forces are measured using FlexiForce® force sensors. The experimental data are analyzed and used to estimate the constitutive parameters of the separation mechanism. Here, the separation mechanism is modeled based on the concept of cohesive zone model (CZM) that is well-studied in the field of fracture mechanics. By using the experimentally measured pulling-up force, this paper proposes a very efficient inverse technique to estimate the constitutive parameters for the CZM. The constitutive laws for the CZM facilitate in relating the separation force at the interface between the cured part and the resin vat in terms of the pulling-up velocity. Unlike work proposed earlier, computationally expensive full-scale finite element runs are not essential in the current work while estimating the required parameters of the constitutive laws. Instead, mechanics-based computationally efficient surrogate model is proposed to readily estimate these constitutive parameters.

Findings

Two constitutive laws are compared on the basis of their predictions of the separation force profile. Excellent match is obtained between the measured and the predicted separation force profiles.

Originality/value

This paper selects a suitable mechanics-based model that can characterize the separation process and proposes a computationally efficient scheme to estimate the required constitutive parameters. The proposed scheme can be used to reliably predict the separation force for the constrained-surface SLA process, leading to improved productivity and reliability of the SLA processes in fabricating the built-up parts.

Details

Rapid Prototyping Journal, vol. 23 no. 4
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 6 November 2017

Leshi Shu, Ping Jiang, Li Wan, Qi Zhou, Xinyu Shao and Yahui Zhang

Metamodels are widely used to replace simulation models in engineering design optimization to reduce the computational cost. The purpose of this paper is to develop a…

Abstract

Purpose

Metamodels are widely used to replace simulation models in engineering design optimization to reduce the computational cost. The purpose of this paper is to develop a novel sequential sampling strategy (weighted accumulative error sampling, WAES) to obtain accurate metamodels and apply it to improve the quality of global optimization.

Design/methodology/approach

A sequential single objective formulation is constructed to adaptively select new sample points. In this formulation, the optimization objective is to select a sample point with the maximum weighted accumulative predicted error obtained by analyzing data from previous iterations, and a space-filling criterion is introduced and treated as a constraint to avoid generating clustered sample points. Based on the proposed sequential sampling strategy, a two-step global optimization approach is developed.

Findings

The proposed WAES approach and the global optimization approach are tested in several cases. A comparison has been made between the proposed approach and other existing approaches. Results illustrate that WAES approach performs the best in improving metamodel accuracy and the two-step global optimization approach has a great ability to avoid local optimum.

Originality/value

The proposed WAES approach overcomes the shortcomings of some existing approaches. Besides, the two-step global optimization approach can be used for improving the optimization results.

Details

Engineering Computations, vol. 34 no. 8
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 25 March 2019

Ji Cheng, Ping Jiang, Qi Zhou, Jiexiang Hu, Tao Yu, Leshi Shu and Xinyu Shao

Engineering design optimization involving computational simulations is usually a time-consuming, even computationally prohibitive process. To relieve the computational…

Abstract

Purpose

Engineering design optimization involving computational simulations is usually a time-consuming, even computationally prohibitive process. To relieve the computational burden, the adaptive metamodel-based design optimization (AMBDO) approaches have been widely used. This paper aims to develop an AMBDO approach, a lower confidence bounding approach based on the coefficient of variation (CV-LCB) approach, to balance the exploration and exploitation objectively for obtaining a global optimum under limited computational budget.

Design/methodology/approach

In the proposed CV-LCB approach, the coefficient of variation (CV) of predicted values is introduced to indicate the degree of dispersion of objective function values, while the CV of predicting errors is introduced to represent the accuracy of the established metamodel. Then, a weighted formula, which takes the degree of dispersion and the prediction accuracy into consideration, is defined based on the already-acquired CV information to adaptively update the metamodel during the optimization process.

Findings

Ten numerical examples with different degrees of complexity and an AIAA aerodynamic design optimization problem are used to demonstrate the effectiveness of the proposed CV-LCB approach. The comparisons between the proposed approach and four existing approaches regarding the computational efficiency and robustness are made. Results illustrate the merits of the proposed CV-LCB approach in computational efficiency and robustness.

Practical implications

The proposed approach exhibits high efficiency and robustness in engineering design optimization involving computational simulations.

Originality/value

CV-LCB approach can balance the exploration and exploitation objectively.

Details

Engineering Computations, vol. 36 no. 3
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 9 July 2019

Chi Zhou, Geni Xu and Zhibing Liu

Internet referral services are a common form of online marketing operating activities. To incentivize infomediaries and improve referral performance, brand retailers…

Abstract

Purpose

Internet referral services are a common form of online marketing operating activities. To incentivize infomediaries and improve referral performance, brand retailers typically apply the cost-per-click (CPC) or the cost-per-sale (CPS) payments. The purpose of this paper is to investigate the effect of referral services on the optimal contract with CPC or CPS payments.

Design/methodology/approach

This paper studies a mechanism design problem for internet referral services. To maximize the expected utility of the brand retailer, an uncertain contract model is established in which the brand retailer's assessment of the infomediary's referral service capability is characterized as an uncertain variable. Then equivalent models under CPC and CPS payments are presented to obtain the optimal solutions.

Findings

The results demonstrate that under CPC payments, as the referral service capability increases, the optimal sales volume is increasing, and the optimal transfer payment first shows a declining and then a rising trend. The brand retailer is less likely to raise the optimal transfer payment for the infomediary given a higher CPC revenue-sharing fee percentage, which is counterintuitive. Under CPS payments, the optimal sales volume and transfer payment are also increasing in the referral service capability. In addition, an increase in the click-through rate leads to the infomediary's incremental marginal utility.

Originality/value

The value of this research is its application of incentive contracts to the internet referral services considering CPC or CPS payments. The results of this research can serve as a guide for retailers and infomediaries in their decision-making around online retailing.

Article
Publication date: 10 June 2021

Wei Liu, Jing Wei Li and Qi Wei Zhou

From a functionalist perspective, this study aims to examine empirically how positive and negative emotions can exert influence on creativity in the workplace. This study…

Abstract

Purpose

From a functionalist perspective, this study aims to examine empirically how positive and negative emotions can exert influence on creativity in the workplace. This study built and tested a theoretical framework that delineates the effect of emotions on employee creativity through different learning mechanisms.

Design/methodology/approach

Field surveys were conducted in a Chinese company and data were collected from 340 employee-supervisor dyads.

Findings

The results indicate that positive emotions were positively related to task-related learning and interactional learning, both of which promote employee creativity. Task-related learning mediated the association between positive emotions and creativity. Nevertheless, negative emotions hindered employees from interactional learning and were negatively associated with creativity. Interactional learning mediated the association between negative emotions and creativity. Moreover, the interaction between positive and negative emotions was negatively associated with task-related learning.

Originality/value

This study contributes to the literature on emotions and employee learning by demonstrating the value of using a functionalist perspective through different procedural mechanisms for employee outcomes and exploring the mediation effects of different learning behaviors in promoting creativity.

Details

Chinese Management Studies, vol. 16 no. 2
Type: Research Article
ISSN: 1750-614X

Keywords

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