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Point Cloud Measurement of Rubber Tread Dimension Based on RGB-Depth Camera

APPLIED SCIENCES-BASEL 2024年第15期14卷 6625页

作者： Huang, Luobin Chen, Mingxia Peng, Zihao Guilin Univ Technol Educ Dept Guangxi Zhuang Autonomous Reg Guilin 541006 Peoples R China Guilin Univ Technol Guangxi Engn Res Ctr Intelligent Rubber Equipment Guilin 541006 Peoples R China Guilin GLESI Sci Technol Co Ltd Guilin 541004 Peoples R China

To achieve an accurate measurement of tread size after fixed-length cutting, this paper proposes a point-cloud-based tread size measurement method. Firstly, a mathematical model of corner points and a reprojection error is established, and the optimal solution of the number of corner points is determined by the non-dominated sorting genetic algorithm ii (NSGA-ii), which reduces the reprojection error of the RGB-D camera. Secondly, to address the problem of the low accuracy of the traditional pixel metric ratio measurement method, the random sampling consensus point cloud segmentation algorithm (RANSAC) and the oriented bounding box (OBB) collision detection algorithm are introduced to complete the accurate detection of the tread size. By comparing the absolute error and relative error data of several groups of experiments, the accuracy of the detection method in this paper reaches 1 mm, and the measurement deviation is between 0.14% and 2.67%, which is in line with the highest accuracy standard of the national standard. In summary, the RGB-D visual inspection method constructed in this paper has the characteristics of low cost and high inspection accuracy, which is a potential solution to enhance the pickup guidance of tread size measurement.

关键词： RGB-depth non-dominated sorting genetic algorithm-ii random sample consensus point cloud segmentation algorithm point cloud registration tread size measurement

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Development of flexible grouting material for cement-stabilized macadam base using response surface and genetic algorithm optimization methodologies

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CONSTRUCTION AND BUILDING MATERIALS 2023年 409卷

作者： Lu, Haonan Dong, Qiao Yan, Shiao Chen, Xueqin Wang, Xiang Southeast Univ Sch Transportat Dept Roadway Engn Nanjing Jiangsu Peoples R China Nanjing Univ Sci & Technol Dept Civil Engn Nanjing Jiangsu Peoples R China Southeast Univ Natl Demonstrat Ctr Expt Rd & Traff Engn Educ Nanjing Jiangsu Peoples R China

To repair the voids and cracks in the Cement-stabilized macadam base (CSMB), a grouting material with lower elastic modulus, enhanced fluidity and slight expansion called Flexible Grouting Material (FGM) was developed using superfine cement, fly ash (FA), silica fume (SF), vinyl acetate-ethylene (VAE) copolymer emulsion, and polyvinyl alcohol (PVA) fiber. After that, the study optimized the proportion of FGM using Response Surface Methodology (RSM) and non-dominated sorting genetic algorithm-ii (NSGA-ii) in Multi-Objective Optimization (MOO). Firstly, to determine the component contents for subsequent experiments, the fluidity, setting time, compressive/flexural strength (1d + 3d), and ratio of compressive strength to flexural strength (C/F, 1d + 3d) were tested. Subsequently, the Response Surface Methodology-Box Behnken Design (RSM-BBD) was employed using VAE content, PVA content, and water-to-cement ratio (W/C) as factors. Additionally, the fluidity, setting time, compressive/flexural strength and C/F (28d), elastic modulus (28d), and drying shrinkage (28d) were considered as responses in RSM-BBD. The VAE content and W/C significantly influenced the response values, while the PVA content had a relatively minor influence. Finally, the NSGA-ii was utilized to determine the optimal proportion of FGM. Compared to the control group, the optimal FGM demonstrated 16.53 % increase in fluidity, 37.86 % decrease in elastic modulus (28d), 47.98 % decrease in C/F (28d), 22.22 % reduction in drying shrinkage (28d), and 54.07 % increase in final setting time.

关键词： Grouting material Flexibility Cement-stabilized macadam base Response Surface Methodology non-dominated sorting genetic algorithm-ii

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MULTI-OBJECTIVE ROBUST PRODUCTION PLANNING CONSIDERING WORKFORCE EFFICIENCY WITH A METAHEURISTIC SOLUTION APPROACH

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INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE 2023年第1期30卷 32-50页

作者： Zeidabadi, Sepideh Asadi Nik, Ebrahim Rezaee Hejazi, Taha-Hossein Sadjad Univ Technol Mashhad Dept Ind Engn Mashhad Iran Amirkabir Univ Technol Dept Ind Engn Garmsar Campus Garmsar Iran

Timely delivery of products to customers is one of the main factors of customer satisfaction and a key to the survival of a manufacturing system. Therefore, decreasing wasted time in manufacturing processes significantly affects production delivery time, which can be achieved through the maximization of workforce efficiency. This issue becomes more complicated when the parameters of the production system are under uncertainty. This paper presents a bi-objective scenario -based robust production planning model considering maximizing workforce efficiency and minimizing costs where the backorder, demand, and costs are uncertain. Also, backorder, raw materials purchasing, inventory control, and manufacturing time capacity are considered. A case study in a faucet manufacturing plant is considered to solve the model. Furthermore, the epsilon-constraint method, the non-dominated sorting genetic algorithm-ii (NSGA-ii), the Strength Pareto Evolutionary algorithm 2 (SPEA2), and the Pareto Envelope-based Selection algorithm ii (PESA-ii) are employed to solve the model. Also, the Taguchi method is used to tune the parameters of these algorithms. To compare these algorithms, five indicators are defined. The results show that the SPEA2 is the most time-consuming algorithm and the NSGA-ii is the fastest, while their objective function values are nearly the same.

关键词： Multi-objective Production Planning Robust Optimization Workforce Efficiency non-dominated sorting genetic algorithm-ii Strength Pareto Evolutionary algorithm 2 Pareto Envelope-based Selection algorithm ii

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MULTI-OBJECTIVE INVENTORY AND ROUTING MODEL FOR A MULTI- PRODUCT AND MULTI-PERIOD PROBLEM OF VETERINARY DRUGS

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INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE 2022年第4期29卷 464-486页

作者： Bardeji, Saeideh Farajzadeh Fakoor, Amir Mohammad Mirghaderi, Seyed-Hadi Ferdowsi Univ Mashhad FUM Dept Management Mashhad Iran Shiraz Univ Dept Management Shiraz Iran

In this study, a multi-objective, multi-product, and multi-period inventory management and routing model was designed for perishable products with a focus on veterinary drugs. The proposed model is a four-objective model to achieve a balance between the costs of drug distribution. The first and second objective functions are related to inventory management, covering inventory costs and demand forecast error, respectively. The third and fourth objective functions involve routing to minimize the transportation costs and greenhouse gas emissions, respectively. Data on three types of drugs were collected for 25 periods (weeks) from one drug distribution center and nine pharmacies in Iran. non-dominated sorting genetic algorithm-ii was employed to find a satisfactory solution. The meta-heuristic method was combined with a Multi-layer Perceptron artificial neural network algorithm to forecast the demand. The model was implemented in MATLAB software. The results show the ability of the proposed model and algorithm to find high-quality solutions.

关键词： Inventory Management and Routing Veterinary Drug Multi-Objective Multi-Product and Multi-Period Model non-dominated sorting genetic algorithm-ii Multi-Layer Perceptron Artificial Neural Network

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Optimizing perishable food products across states: A multi objective evolutionary algorithm for surplus to deficit transportation

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2024年第PartA期137卷

作者： Karanam, Malleswari Krishnanand, Lanka Manupati, Vijaya Kumar Varela, M. L. R. NIT Dept Mech Engn Warangal 506004 Telangana India Indian Inst Management Operat & Supply Chain Div Mumbai 400087 India Univ Minho Dept Prod & Syst Guimaraes Portugal

Ensuring the seamless flow of goods from farmer to stakeholder is paramount especially considering the facts such as demand fluctuations, quantity availability, vehicle capacity, inventory limits and truck preferences. In this paper, we proposed a mixed integer linear programming (MILP) model for distributing perishable food goods from surplus states to surplus and deficit state wholesalers in the Indian subcontinent, with the goal of minimizing total cost (fixed, variable, and operational) and transportation time. To ensure product delivery on time, we looked at various scenarios including a case with real-life constraints. Solving this computationally complex task with conflicting objectives in a reasonable time is difficult. To handle the aforementioned multi-objective problem, we proposed an evolutionary algorithm based modified non-dominated sorting genetic algorithm ii (MNSGA-ii). Furthermore, the suggested algorithm's performance is tested against the most extensively used multi-objective algorithm, non-dominated sorting genetic method-ii (NSGA-ii). According to the findings, the proposed MNSGA-ii outperforms practically all instances.

关键词： Perishable food Multi-objective Evolutionary algorithm Mixed integer linear programming non-dominated sorting genetic algorithm-ii Modified non-dominated sorting genetic algo- rithm-ii

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Operation and Multi-Objective Design Optimization of a Plate Heat Exchanger with Zigzag Flow Channel Geometry

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ENERGIES 2022年第21期15卷 8205-8205页

作者： Chen, Wei-Hsin Li, Yi-Wei Chang, Min-Hsing Chueh, Chih-Che Ashokkumar, Veeramuthu Saw, Lip Huat Natl Cheng Kung Univ Dept Aeronaut & Astronaut Tainan 701 Taiwan Tunghai Univ Res Ctr Smart Sustainable Circular Econ Taichung 407 Taiwan Natl Chin Yi Univ Technol Dept Mech Engn Taichung 411 Taiwan Tatung Univ Dept Mech & Mat Engn Taipei 104 Taiwan Saveetha Univ Saveetha Dent Coll Ctr Transdisciplinary ResDept Pharmacol Saveetha Inst Med & Tech SciBiorefineries Biofue Chennai 600077 Tamil Nadu India Tunku Abdul Rahman Univ Lee Kong Chian Fac Engn & Sci Kajang 43000 Malaysia

The performance of a plate heat exchanger (PHE) using water as the working fluid with zigzag flow channels was optimized in the present study. The optimal operating conditions of the PHE are explored experimentally by the Taguchi method, with effectiveness as the objective function. The results are further verified by the analysis of variance (ANOVA). In addition, the zigzag flow channel geometry is optimized by the non-dominated sorting genetic algorithm-ii (NSGA-ii), in which the effectiveness and pressure drop of the PHE are considered the two objective functions in the multi-objective optimization process. The experimental results show that the ratio of flow rates is the most important factor affecting the effectiveness of the PHE. The optimal operating conditions are the temperatures of 95 degrees C and 10 degrees C at the inlets of hot and cold water flows, respectively, with a cold/hot flow rate ratio of 0.25. The resultant effectiveness is 0.945. Three geometric parameters of the zigzag flow channel are considered, including the entrance length, the bending angle, and the fillet radius. The sensitivity analysis of the parameters reveals that a conflict exists between the two objective functions, and multi-objective optimization is necessary for the zigzag flow channel geometry. The numerical simulations successfully obtain the Pareto optimal front for the two objective functions, which benefits the determination of the geometric design for the zigzag flow channel.

关键词： plate heat exchanger Taguchi method analysis of variance zigzag flow channel multi-objective optimization non-dominated sorting genetic algorithm-ii

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Surrogate-Based Multiobjective Optimization of Detention Pond Volume in Sponge City

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WATER 2023年第15期15卷 2705-2705页

作者： Yang, Yuanyuan Xin, Yanfei Li, Jiake Xian Univ Technol State Key Lab Ecohydraul Northwest Arid Reg China Xian 710048 Peoples R China

Detention ponds are effective structures for stormwater management in the urban drainage system of sponge cities. The pond size is taken as the decision variable, while the cost, total suspended solids (TSS), and catchment peak outflow (CPO) serve as the objectives for optimizing the detention pond volume. First, we randomly generated 10,000 pond areas and input them into the stormwater management model to simulate the time series of outflow and suspended solids concentration, thereby generating samples by combining the set of pond area, corresponding cost, TSS, and CPO. Then, two backpropagation neural network models (i.e., BPNN-TSS and BPNN-CPO) were trained, tested, and evaluated for predicting TSS and CPO, respectively. We employed them as surrogates and used the non-dominated sorting genetic algorithm-ii to solve the optimization problem. The results showed: (1) The BPNN models accurately predicted TSS and CPO (determination coefficient 0.988 +/- 0.996, Nash-Sutcliffe efficiency 0.988 +/- 0.997), and efficiently substituted stormwater management model simulations for optimization purposes (residuals -18.49 +/- 28.10 kg and -0.45 +/- 0.29 m(3)/s). (2) For the Pareto solutions, the detention pond reduced TSS by 0 +/- 8.33% and CPO by 0 +/- 72.44% and delayed their peaks by 4 +/- 52 min;the reduction in TSS and CPO tends to grow as pond size increases, and CPO reduction exhibits a minor marginal effect. (3) The surrogate-based approach saves 90.03% runtime while preserving the quality of the Pareto solutions, verifying reliability.

关键词： backpropagation neural network non-dominated sorting genetic algorithm-ii peak outflow stormwater drainage system suspended solids SWMM

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Optimal design of heating system for electrical rapid heat cycle mold based on multi-objective optimization, multiple-attribute decision-making, and conformal design theory

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ADVANCES IN MECHANICAL ENGINEERING 2018年第8期10卷

作者： Li, Jiquan Li, Taidong Peng, Xiang Liu, Feng Zhou, Hangchao Jiang, Shaofei Zhejiang Univ Technol Minist Educ Key Lab E&M Hangzhou 310014 Zhejiang Peoples R China Zhejiang Univ Water Resources & Elect Power Sch Mech & Automot Engn Hangzhou Zhejiang Peoples R China

To improve the heating efficiency and cavity surface temperature uniformity, an optimal design method was developed for the heating system in electrical rapid heat cycle molding mold. First, an electrical rapid heat cycle molding mold was simplified as a single heating cell unit for thermal response analysis based on conformal design theory. Second, a response surface using back propagation neural network was constructed on the ground of initial finite element experiments. Then, a non-dominated sorting genetic algorithm-ii combined with the polynomial back propagation neural network model was proposed to capture the Pareto-optimal solutions. Subsequently, the technique for order preference by similarity to ideal solution based on entropy-based weight was adopted as a multi-attribute decision-making method to choose the trade-off optimal design point from the Pareto-optimal set. To gain the optimal design of heating system, the optimized heating cell unit for electrical rapid heat cycle molding mold was calculated and finally mapped into the entire mold. Cavity surface temperature uniformity increased by 17.1%, and heating efficiency increased by 26%. The results show that the temperature distribution uniformity on the mold cavity surface was obviously improved and using this optimization strategy ensured high heating efficiency.

关键词： Electrical rapid heat cycle molding heating cell unit back propagation neural network non-dominated sorting genetic algorithm-ii technique for order preference by similarity to ideal solution

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Multi-objective flexible job-shop scheduling problem with improved NSGA2 algorithm

Multi-objective flexible job-shop scheduling problem with im...

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第43届中国控制会议

作者： Hongyi Xu Minyun Li School of Engineering Hu Zhou University School of Intelligent Manufacturing Hu Zhou College

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Aiming at the situation of low scheduling efficiency resulting in resource waste in multi-objective flexible job-shop, this paper proposes an improved elitist non-dominated sorting genetic algorithm-ii(NSGA2). A population initialization method is designed based on three optimization objectives. At the same time, the individual fitness is defined according to the individual objective funtion and crowding distance. A parameter adaptive strategy is proposed to realize the adaptability of individual crossover and mutation probability. In the process of optimization, the Beetle Antennae Search(BAS) is used to carry out a second search on the dominated population to improve the single individual search speed of the algorithm and avoid falling into local optimal. Finally, the algorithm is verified on the classic Kacem dataset and the actual production case of the enter-prise, the experimental results show that the proposed method is superior to the existing methods, which proves the feasibility of the algorithm in multi-objective flexible job-shop scheduling problem.

关键词： Adaptive non-dominated sorting genetic algorithm-ii Beetle Antennae Search Initialization

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