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An improved artificial bee colony algorithm with MaxTF heuristic rule for two-sided assembly line balancing

Xiaokun DUAN, Bo WU, Youmin HU, Jie LIU, Jing XIONG

Frontiers of Mechanical Engineering 2019, Volume 14, Issue 2,   Pages 241-253 doi: 10.1007/s11465-018-0518-6

Abstract: This paper proposes an improved artificial bee colony (IABC) algorithm with the MaxTF heuristic rule.In the heuristic initialization process, the MaxTF rule defines a new task’s priority weight.The experimental results demonstrate that the proposed MaxTF rule performs better than other heuristicrules, as it can find the best solution for all the 10 test cases.

Keywords： two-sided assembly line balancing problem     artificial bee colony algorithm     heuristic rules     time boundary    

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A job-insertion heuristic for minimizing the mean flowtime in dynamic flowshops

Guang GUO, Bo WU, Shuzi YANG

Frontiers of Mechanical Engineering 2011, Volume 6, Issue 2,   Pages 197-202 doi: 10.1007/s11465-011-0211-5

Abstract:

A new adaptive job-insertion based heuristic is presented to minimize the mean flowtime in a dynamicThe heuristic is derived by inserting new jobs into the scheduled sequence as needed when the machineComputation results indicate that the proposed heuristic performs 2.7%–10.8% better than the SPT

Keywords： scheduling     dynamic flowshops     flowtime     heuristic     mean flowtime    

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Enterprise-wide optimization of integrated planning and scheduling for refinery-petrochemical complex with heuristic

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 10,   Pages 1516-1532 doi: 10.1007/s11705-022-2283-7

Abstract: To solve the problem efficiently, a heuristic algorithm combined with a convolutional neural networkCNN input, leading to the integration of a data-driven approach and classical optimization by which a heuristic

Keywords： planning     scheduling     refinery-petrochemical     convolutional neural network     heuristic algorithm    

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Analysis of dispatching rules in a stochastic dynamic job shop manufacturing system with sequence-dependent

Pankaj SHARMA,Ajai JAIN

Frontiers of Mechanical Engineering 2014, Volume 9, Issue 4,   Pages 380-389 doi: 10.1007/s11465-014-0315-9

Abstract: This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow timeNine dispatching rules identified from literature are incorporated in the simulation model.

Keywords： scheduling     stochastic dynamic job shop     sequence-dependent setup times     dispatching rule     simulation    

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Determination of a suitable index for a solvent via two-column extractive distillation using a heuristic

Zhaoyou Zhu, Guoxuan Li, Yao Dai, Peizhe Cui, Dongmei Xu, Yinglong Wang

Frontiers of Chemical Science and Engineering 2020, Volume 14, Issue 5,   Pages 824-833 doi: 10.1007/s11705-019-1867-3

Abstract: This work presents a heuristic method for selecting the optimal solvent to minimize the total annual

Keywords： heuristic method     solvent selection     extractive distillation     total annual cost    

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An efficient two-stage approach for structural damage detection using meta-heuristic algorithms and group

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 4,   Pages 907-929 doi: 10.1007/s11709-020-0628-1

Abstract: In this study, the performance of an efficient two-stage methodology which is applied in a damage detection system using a surrogate model of the structure has been investigated. In the first stage, in order to locate the damage accurately, the performance of the modal strain energy based index for using different numbers of natural mode shapes has been evaluated using the confusion matrix. In the second stage, to estimate the damage extent, the sensitivity of most used modal properties due to damage, such as natural frequency and flexibility matrix is compared with the mean normalized modal strain energy (MNMSE) of suspected damaged elements. Moreover, a modal property change vector is evaluated using the group method of data handling (GMDH) network as a surrogate model during damage extent estimation by optimization algorithm; in this part of methodology, the performance of the three popular optimization algorithms including particle swarm optimization (PSO), bat algorithm (BA), and colliding bodies optimization (CBO) is examined and in this regard, root mean square deviation ( ) based on the modal property change vector has been proposed as an objective function. Furthermore, the effect of noise in the measurement of structural responses by the sensors has also been studied. Finally, in order to achieve the most generalized neural network as a surrogate model, GMDH performance is compared with a properly trained cascade feed-forward neural network (CFNN) with log-sigmoid hidden layer transfer function. The results indicate that the accuracy of damage extent estimation is acceptable in the case of integration of PSO and MNMSE. Moreover, the GMDH model is also more efficient and mimics the behavior of the structure slightly better than CFNN model.

Keywords： two-stage method     modal strain energy     surrogate model     GMDH     optimization damage detection    

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Space-time evolution rules study on acoustic emission location in rock under cyclic loading

Jiang XU, Shuchun LI, Yunqi TAO, Yongdong JIANG, Xiaojun TANG,

Frontiers of Structural and Civil Engineering 2009, Volume 3, Issue 4,   Pages 422-427 doi: 10.1007/s11709-009-0056-8

Abstract: An acoustic emission (AE) location experiment was performed on sandstone using an advanced AE test system. The space-time evolution rule regarding damage was analyzed under cyclic loading as well as AE. The results show that AE on static loading process is consistent with the damage evolution rule of compression and the elastic-plastic deformation phase; at the beginning of cyclic loading with low duration time and energy, AE events came from a small crack. The location result showed that most events occurred in the core zone forming at the static loading process, and the location points changed slowly. AE energy changed little during the metaphase of cyclic process. There was a modest increase of location points in every cycle. The tendency of steady development could be predicted from the AE location events. At the end of each cyclic loading, the quantity of AE events and energy increased quite rapidly, reaching a maximum at the last cycle. AE events had high energy and duration time. Location events changed quite rapidly and assembled and linked continuously in the core zone. At the same time, they expanded to the top of specimen. A macroscopic crack finally formed. In the postfailure process, some AE events still existed due to fracturing of gliding friction. Owing to the inner stress balance of rock even after loading stopped, minor AE events still occurred.

Keywords： location result     AE location     consistent     friction     elastic-plastic deformation    

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Rules Auto-conditioning Fuzzy Controller

Cheng Jin,Zhang Chenghui,Xia Dongwei

Strategic Study of CAE 2003, Volume 5, Issue 9,   Pages 78-81

Abstract:

According to the fuzzy theory and practical experience, the authors propose a rules autoconditioning

Keywords： fuzzy controller     rules auto-tuning     adaptive    

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The prior rules of designing Ti

Yingying Jian, Danyao Qu, Lihao Guo, Yujin Zhu, Chen Su, Huanran Feng, Guangjian Zhang, Jia Zhang, Weiwei Wu, Ming-Shui Yao

Frontiers of Chemical Science and Engineering 2021, Volume 15, Issue 3,   Pages 505-517 doi: 10.1007/s11705-020-2013-y

Abstract: However, their designing rules are still lacking critical thinking from the viewpoint of the intrinsicThese two rules are demonstrated, and could be considered with priority both in the future researches

Keywords： MXene based sensor     prior     reducing gases     oxidizing gases    

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Words alignment based on association rules for cross-domain sentiment classification None

Xi-bin JIA, Ya JIN, Ning LI, Xing SU, Barry CARDIFF, Bir BHANU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 2,   Pages 260-272 doi: 10.1631/FITEE.1601679

Abstract: In this paper, we propose a novel approach called words alignment based on association rules (WAAR) forrelationship between domain-specific words in different domains by learning the strong association rules

Keywords： Sentiment classification     Cross-domain     Association rules    

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New US Rules Promise to Unlock Hearing Aid Availability

Mitch Leslie

Engineering 2022, Volume 14, Issue 7,   Pages 7-9 doi: 10.1016/j.eng.2022.05.008

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Overall HIEs deconstruction method and its application

Li LIN, Chengqi XUE,

Frontiers of Mechanical Engineering 2009, Volume 4, Issue 4,   Pages 466-471 doi: 10.1007/s11465-009-0076-z

Abstract: A mobile phone is taken as the research subject, the emotional design rules are inferred based on the

Keywords： product design     relationship model     human interface     design rules     emotion    

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Recent advances in system reliability optimization driven by importance measures

Shubin SI, Jiangbin ZHAO, Zhiqiang CAI, Hongyan DUI

Frontiers of Engineering Management 2020, Volume 7, Issue 3,   Pages 335-358 doi: 10.1007/s42524-020-0112-6

Abstract: The rules for simple optimization problems are summarized to enhance system reliability by using rankingor heuristic methods based on IMs.

Keywords： importance measure     system performance     reliability optimization     optimization rules     optimization algorithms    

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Characterization of hidden rules linking symptoms and selection of acupoint using an artificial neural

Won-Mo Jung, In-Soo Park, Ye-Seul Lee, Chang-Eop Kim, Hyangsook Lee, Dae-Hyun Hahm, Hi-Joon Park, Bo-Hyoung Jang, Younbyoung Chae

Frontiers of Medicine 2019, Volume 13, Issue 1,   Pages 112-120 doi: 10.1007/s11684-017-0582-z

Abstract: Comprehension of the medical diagnoses of doctors and treatment of diseases is important to understand the underlying principle in selecting appropriate acupoints. The pattern recognition process that pertains to symptoms and diseases and informs acupuncture treatment in a clinical setting was explored. A total of 232 clinical records were collected using a Charting Language program. The relationship between symptom information and selected acupoints was trained using an artificial neural network (ANN). A total of 11 hidden nodes with the highest average precision score were selected through a tenfold cross-validation. Our ANN model could predict the selected acupoints based on symptom and disease information with an average precision score of 0.865 (precision, 0.911; recall, 0.811). This model is a useful tool for diagnostic classification or pattern recognition and for the prediction and modeling of acupuncture treatment based on clinical data obtained in a real-world setting. The relationship between symptoms and selected acupoints could be systematically characterized through knowledge discovery processes, such as pattern identification.

Keywords： acupuncture     indication     neural network     pattern identification     prediction    

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Prediction of hydro-suction dredging depth using data-driven methods

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 3,   Pages 652-664 doi: 10.1007/s11709-021-0719-7

Abstract: In this study, data-driven methods (DDMs) including different kinds of group method of data handling (GMDH) hybrid models with particle swarm optimization (PSO) and Henry gas solubility optimization (HGSO) methods, and simple equations methods were applied to simulate the maximum hydro-suction dredging depth (hs). Sixty-seven experiments were conducted under different hydraulic conditions to measure the hs. Also, 33 data samples from three previous studies were used. The model input variables consisted of pipeline diameter (d), the distance between the pipe inlet and sediment level (Z), the velocity of flow passing through the pipeline (u0), the water head (H), and the medium size of particles (D50). Data-driven simulation results indicated that the HGSO algorithm accurately trains the GMDH methods better than the PSO algorithm, whereas the PSO algorithm trained simple simulation equations more precisely. Among all used DDMs, the integrative GMDH-HGSO algorithm provided the highest accuracy (RMSE = 7.086 mm). The results also showed that the integrative GMDHs enhance the accuracy of polynomial GMDHs by ~14.65% (based on the RMSE).

Keywords： sedimentation     water resources     dam engineering     machine learning     heuristic    

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Title Author Date Type Operation

An improved artificial bee colony algorithm with MaxTF heuristic rule for two-sided assembly line balancing

Xiaokun DUAN, Bo WU, Youmin HU, Jie LIU, Jing XIONG

Journal Article

A job-insertion heuristic for minimizing the mean flowtime in dynamic flowshops

Guang GUO, Bo WU, Shuzi YANG

Journal Article

Enterprise-wide optimization of integrated planning and scheduling for refinery-petrochemical complex with heuristic

Journal Article

Analysis of dispatching rules in a stochastic dynamic job shop manufacturing system with sequence-dependent

Pankaj SHARMA,Ajai JAIN

Journal Article

Determination of a suitable index for a solvent via two-column extractive distillation using a heuristic

Zhaoyou Zhu, Guoxuan Li, Yao Dai, Peizhe Cui, Dongmei Xu, Yinglong Wang

Journal Article

An efficient two-stage approach for structural damage detection using meta-heuristic algorithms and group

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

Journal Article

Space-time evolution rules study on acoustic emission location in rock under cyclic loading

Jiang XU, Shuchun LI, Yunqi TAO, Yongdong JIANG, Xiaojun TANG,

Journal Article

Rules Auto-conditioning Fuzzy Controller

Cheng Jin,Zhang Chenghui,Xia Dongwei

Journal Article

The prior rules of designing Ti

Yingying Jian, Danyao Qu, Lihao Guo, Yujin Zhu, Chen Su, Huanran Feng, Guangjian Zhang, Jia Zhang, Weiwei Wu, Ming-Shui Yao

Journal Article

Words alignment based on association rules for cross-domain sentiment classification

Xi-bin JIA, Ya JIN, Ning LI, Xing SU, Barry CARDIFF, Bir BHANU

Journal Article

New US Rules Promise to Unlock Hearing Aid Availability

Mitch Leslie

Journal Article

Overall HIEs deconstruction method and its application

Li LIN, Chengqi XUE,

Journal Article

Recent advances in system reliability optimization driven by importance measures

Shubin SI, Jiangbin ZHAO, Zhiqiang CAI, Hongyan DUI

Journal Article

Characterization of hidden rules linking symptoms and selection of acupoint using an artificial neural

Won-Mo Jung, In-Soo Park, Ye-Seul Lee, Chang-Eop Kim, Hyangsook Lee, Dae-Hyun Hahm, Hi-Joon Park, Bo-Hyoung Jang, Younbyoung Chae

Journal Article

Prediction of hydro-suction dredging depth using data-driven methods

Journal Article