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6th International Symposium on Electrical and Electronics Engineering (ISEEE)

作者： Pop, Mihai Avram, Camelia Domuta, Claudiu Radu, Dan Astilean, Adina TUCN Automat Dept Cluj Napoca Romania

ISBN: (纸本)9781728129068

The paper proposes a route planning strategy integrated in a software platform, capable to offer personalized visiting program for touristic zones. The presented solution is based on the utilization of multimodal intelligent transportation systems, having the potential to contribute to the development of smart low-carbon cities. The considered approach is based on two different routing algorithms: an exact one, the Martins algorithm, applied for the initial scheduling of the travel and nsga-ii, and a faster metaheuristic algorithm to tackle momentary modifications generated by new decisions and unexpected events. The multi-objective scheduling strategy was implemented and tested for medium, time dependent transport networks. In order to develop smart tourism services, the platform also integrates the conceptual and implementation support offered by cloud computing.

关键词： smart tourism cloud computing routing algorithms Martins algorithm nsga-ii algorithm

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MULTI-OBJECTIVE HYDRAULIC OPTIMIZATION ON INTAKE DUCT OF WATER-JET PROPULSION USING nsga-ii 8

MULTI-OBJECTIVE HYDRAULIC OPTIMIZATION ON INTAKE DUCT OF WAT...

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ASME-JSME-KSME Joint Fluids Engineering Conference (AJK-FED)

作者： Zhu, Rui Cao, Puyu Wang, Yang Ning, Chao Jiangsu Univ Res Ctr Fluid Machinery Engn & Technol Zhenjiang Jiangsu Peoples R China

ISBN: (纸本)9780791859049

Flow distortions occur at the outlet section of the intake duct owing to its shape properties, which is a component of water jet propulsion. Since the noticeable influence of intake's flow characteristics upon propulsive efficiency, it's necessary to focus on intake duct redesign. In this paper, a systematic methodology for reducing flow distortions and power losses within the intake duct through a shape optimization process was obtained. In addition, the mechanism of flow distortions was also developed. The flush type inlet applied in the marine vessel with the speed of 30 knots was chosen as research project. Four characteristic parameters were set as optimization variables depending on the geometrical relationship of thirteen characteristic parameters referred to the duct longitudinal midsection, which were the ramp angle alpha, the radius of the upper lip R-3, the radius of the lower lip R-4 and the lip height h respectively. Subsequently, a sample space was built by Latin Hypercube Sampling (LHS) and the parameters were normalized in the range of 0 to I. With the commercial software CFX, the numerical simulation was accomplished driven by SST k-omega turbulence model. Multi-objective optimization based on the Non-Dominated Sorting Genetic algorithm ii (nsga-ii) was utilized to minimize the non-uniformity at outlet section and maximize the minimal pressure at lip simultaneously. Moreover, the Radial Basis Function (RBF) neural network was employed to approximate the functional relationship between variables and objectives, which could be applied in the nsga-ii to get the Pareto Front. The minimum non-uniformity point and the trade-off point (The point both satisfies the minimum non-uniformity and the maximum minimal pressure at lip strategically) were selected from the Pareto Front. With regard to the characteristic parameters of the trade-off point, the ramp angle, the radius of the upper lip, the radius of the lower lip and the lip height are 31.91 degrees, 11

关键词： intake duct water-jet propulsion nsga-ii algorithm multi-objective optimization

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Bi-objective Optimization Model for Assembly Line Balancing with Worker Satisfaction 16

Bi-objective Optimization Model for Assembly Line Balancing ...

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16th International Conference on Service Systems and Service Management (ICSSSM)

作者： Liu, Ming Liu, Xin Liu, Zhongzheng Tongji Univ Sch Econ & Management Shanghai Peoples R China

ISBN: (纸本)9781728119410

This paper considers a joint problem of assigning workers and balancing assembly line, considering worker satisfaction. Two important managerial objectives are the minimisation of the cycle time and the maximisation of the worker satisfaction. With the perfection of labor protection law, production enterprises cannot only consider the production efficiency of the company in the process of organizing production, but also take into account the satisfaction of workers. Different workers usually have different preferences for different types of operations. Therefore, production enterprises need to consider different workers'satisfaction with different assembly operations when assigning assembly operations to workers. The main mission of this work is to improve the efficiency of assembly line balancing, that is, to reduce the cycle time, as well as increasing total worker satisfaction. A bi-objective mixed integer linear programming model is proposed. Then epsilon constraint algorithm is developed to verify the correctness and validity of the proposed model. Simultaneously, the framework of nsga-ii algorithm is designed to solve large scale problems in future work.

关键词： Assembly line worker assignment and balancing problem Bi-objective mixed integer linear programming Worker satisfaction Epsilon-constraint method nsga-ii algorithm

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A method for the multi-objective optimization of the operation of natural gas pipeline networks considering supply reliability and operation efficiency

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COMPUTERS & CHEMICAL ENGINEERING 2019年 131卷 106584-000页

作者： Su, Huai Zio, Enrico Zhang, Jinjun Li, Xueyi Chi, Lixun Fan, Lin Zhang, Zongjie China Univ Petr Natl Engn Lab Pipeline Safety MOE Key Lab Petr Engn Beijing Key Lab Urban Oil & Gas Distribut Technol Beijing 102249 Peoples R China Politecn Milan Dipartimento Energia Via La Masa 34 I-20156 Milan Italy PSL Res Univ Mines ParisTech CRC Sophia Antipolis France Petrochina West East Gas Pipeline Dongfushan Rd 458 Shanghai 200122 Peoples R China

Reliable gas supply for minimum risk of supply shortage and minimum power demand for low energy cost are two fundamental objectives of natural gas pipeline networks. In this paper, a multi-objective optimization method is developed to trade-off reliability and power demand in the decision process. In the optimization, the steady state behavior of the natural gas pipeline networks is considered, but the uncertainties of the supply conditions and customer consumptions are accounted for. The multi-objective optimization regards finding operational strategies that minimize power demand and risk of gas supply shortage. To quantify the probability of supply interruption in pipeline networks, a novel limit function is introduced based on the mass conservation equation. Then, the risk of interruption is calculated by combining the probability of interruption and its consequences, measured in utility terms. The multiobjective optimization problem is solved by the nsga-ii algorithm and its effectiveness is tested on two typical pipeline networks, i.e., a tree-topology network and a loop-topology network. The results show that the developed optimization model is able to find solutions which effectively compromise the need of minimizing gas supply shortage risk and reducing power demand. Finally, a sensitivity analysis is conducted to analyze the impact of demand uncertainties on the optimization results. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Natural gas pipeline network Multi-objective optimization Supply reliability Power demand nsga-ii algorithm

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Optimization of processing parameters of laser skin welding in vitro combining the response surface methodology with nsga- ii

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INFRARED PHYSICS & TECHNOLOGY 2019年 103卷 103067-000页

作者： Li, Cong Huang, Jun Wang, Kehong Chen, Zibo Liu, Qimeng Nanjing Univ Sci & Technol Sch Mat Sci & Engn Nanjing Jiangsu Peoples R China

Objective: This study aimed to optimize the parameters of laser skin welding by combining the response surface methodology with nsga-ii, so as to achieve the goal of improving the weld strength while causing as little thermal damage as possible. Methods: The response surface methodology was used to design the experiment. The optimization model of laser biological tissue welding process parameters was established, which took the power, pulse frequency and scanning speed of the laser as the optimization variables, the maximum tensile strength of the incision and the peak temperature of skin tissue as the optimization objectives. Meanwhile, the multi-objective nsga-ii algorithm was used to find the optimal solution and obtain the optimal process parameters. Then we carried out experiments to verify the effect of the optimized parameters by comparing with the unoptimized result. Results: The optimized process parameters of laser skin welding were effective to improve the welding quality and achieve full-thickness penetration of the skin tissue. Compared with the non-optimized groups, on the premise of guaranteeing maximum strength, the peak temperature of tissue is reduced. Conclusions: Using the optimized process parameters to weld the skin tissues can obtain higher welding strength and at the same time cause low levels of thermal damage. This also verifies the correctness of the model, which is helpful to improve the adaptability of laser welding to other different tissues and reduce the consumption of time and material.

关键词： Laser welding Skin tissue nsga-ii algorithm Optimization

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Carbon Emission Evaluation Based on Multi-Objective Balance of Sewing Assembly Line in Apparel Industry

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ENERGIES 2019年第14期12卷 2783页

作者： Zhang, Xujing Chen, Yan Soochow Univ Coll Text & Clothing Engn Suzhou 215021 Peoples R China

Apparel manufacturing is an industry with high energy consumption and carbon emissions. With the development of the low-carbon economy, low-carbon production in the apparel manufacturing industry become more and more imperative. The apparel industry is encountering great challenges in reducing carbon emissions. Garment sewing comprises a large number of processes, machines and operators. However, the existing studies lack quantitative analysis of carbon sources in the sewing process. This study analyzed the carbon emission characteristics in garment sewing production. Evaluation models of carbon emission were established for the sewing process in this research and the factors of fabrics, accessories, sewing machines and operators were included in the models. The results showed that fabrics and accessories were the main sources of carbon emissions in garment sewing production. The second largest carbon emission source was sewing machines, followed by operators. According to the evaluation models, the number of machines, operators and the utilization rate of the machines were related to the balance of the assembly line. A multi-objective optimization model aimed at minimizing the time loss rate and smoothness index of the assembly line was established, and a fast and elitist multi-objective genetic algorithm was used to obtain the solution for carbon emission reduction. The men's shirt assembly lines, based on three types of workstation layouts (the order of processes, the type of machines and the components of the garment), were applied to verify the effectiveness of the model and algorithm. The results indicated that the total carbon emissions of the three assembly lines based on balance optimization were less than that of the normal assembly line. The assembly line of the workstations arranged in the order of processes was the best assembly line since it had the highest efficiency and the lowest carbon emissions.

关键词： apparel industry carbon emissions evaluation model assembly line balance nsga-ii algorithm

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Research on Optimal Storage Scheme of Containers in the Port Yard Based on Hydrodynamics 6

Research on Optimal Storage Scheme of Containers in the Port...

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6th International Symposium on Project Management (ISPM)

作者： Dong, Hongjin Zhang, Qi Beijing Jiaotong Univ Sch Traff & Transportat 3 Shangyuancun Beijing 100044 Peoples R China

ISBN: (纸本)9781921712661

This paper converts the container arriving at the port into a truck flow using the theory and method of fluid mechanics, and then to analyze the truck flow's running state on the road. Taking the capacity of the port yard as a "valve" to regulate the flow of container trucks, the running state of the truck flow is changed by adjusting the number of containers entering and exiting the yard. On this basis, a multi-objective optimization model is constructed with the objective of the shortest distribution time and minimum storage cost for containers, so as to obtain the optimal container storage plan. Designing the improved nsga-ii algorithm to solve the model. An empirical research was carried out on the Phase ii terminal of Ningbo Beilun port. And results of this paper verify the accuracy and effectiveness of the model and algorithm.

关键词： container yard capacity fluid mechanics multi-objective optimization nsga-ii algorithm pareto solution

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The objective design of triangular bucket for dam's spillway using Non-dominated Sorting Genetic algorithm ii: nsga-ii

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SCIENTIA IRANICA 2017年第1期24卷 19-27页

作者： Hojjati, S. H. Hojjati, S. H. Neyshabouri, S. A. A. Salehi Tarbiat Modares Univ Fac Civil & Environm Engn Tehran Iran Babol Univ Technol Fac Elect & Comp Engn Babol Sar Iran Tarbiat Modares Univ Fac Civil & Environm Engn Water Engn Res Inst Tehran Iran Amirkabir Univ Fac Civil & Environm Engn Tehran Iran

Ski jump is one of the most effective structures in energy dissipation over spillways. Spillways have long been of practical importance to safety of dams. The major criteria in hydraulic design are based on the analytical and empirical methods. In the current study, in order to increase chute spillway efficiency, a multi-objective evolutionary algorithm known as the Non-dominated Sorting Genetic algorithm ii (nsga-ii) has been utilized to design the optimal triangular bucket angle and chute width. In design method, two separate objective functions have been used. In the first objective function, equations of dynamic pressure of the bucket, the jet length after bucket, and the scour depth have been used. The second objective function is related to construction volume of chute spillway. For calibrating the first objective function, characteristics of Karoon iiI dam have been used as a case study. The difference between design parameters of Karoon iiI spillway and those from nsga-ii algorithm method is less than 12 percent. According to the results, if the jet length is considered as the most impressive parameter in the first objective function, design of the spillway becomes frugal. (C) 2017 Sharif University of Technology. All rights reserved.

关键词： Triangular flip bucket Chute spillway width Ski jump nsga-ii algorithm Karoon iiI dam

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OPTIMIZATION OF MACHINING PROCESS PLANNING FOR CARBON REDUCTION 13

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13th ASME International Manufacturing Science and Engineering Conference

作者： Dong, Zhaorui Liu, Qiong Li, Qin Huazhong Univ Sci & Technol Sch Mech Sci & Engn State Key Lab Digital Mfg Equipment & Technol Wuhan Hubei Peoples R China CATL Ningde Fujian Peoples R China

ISBN: (纸本)9780791851357

Most researches on process planning optimized machining process routings and cutting parameters independently and ignored their comprehensive effects on carbon reduction. In order to further reduce carbon emissions in manufacturing processes, an optimization model of cutting parameters and machining process routings is proposed to minimize total carbon emissions and total processing time of all processes. Carbon emissions include those caused by energy consumptions of machines in cutting state, material consumption of cutting tools and cutting fluid in all processes. As the optimization of cutting parameters is a continuous optimization problem, but the optimization of machining process routings including machining methods, process sequences, machine allocating and cutter selecting are discrete optimization problems, the whole optimization of process planning is divided into two parts. One is continuous optimization of cutting parameters. Another is discrete optimization of machining process routings. A hybrid optimization strategy of bird swarm algorithm (BSA) and nsga- ii algorithm is proposed to optimize the proposed model. Cutting parameters are optimized using BSA aiming at minimizing carbon emissions and machining time of each process. Machining process routings are optimized using nsga- ii under each optimized group of cutting parameters from the Pareto set. Four kinds of mutation operators in nsga- ii are designed for the discrete optimization of machining process routings. A workpiece with six machining features to be machined in a workshop with two CNC lathes, two CNC milling machines and two drilling machines is taken as a case study. The validity of the proposed model and hybrid strategy is verified by computational and analytical results. Several conclusions are yielded.

关键词： Low carbon manufacturing Cutting parameter optimization Process planning Bird swarm algorithm nsga-ii algorithm

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Study on Goods Location Optimization of Automated Warehouses in Pharmaceutical Companies

Study on Goods Location Optimization of Automated Warehouses...

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Chinese Automation Congress (CAC)

作者： Zeng, Qi He, Janjun Hu, Enze Wu, Renchao Cent South Univ Sch Informat Sci & Engn Changsha Hunan Peoples R China

ISBN: (纸本)9781728113128

In the pharmaceutical industry, the profit of the enterprise nowdays is more determined by warehouse cost, which can be significantly reduced by the reasonable distribution of goods. Considering the characteristics of goods (or drugs), a multi-objective optimization mathematical model for goods location is established in this paper. The optimization model is composed of a travel time model based on the input/output (I/O) frequency of goods and the speed change of stacker cranes when conveying goods. Meanwhile, taking into account strong goods correlation, finished products and raw materials are stored by class instead of by area, therefore, a within-class correlation model and a between-class correlation model are also comprised in the optimization model. The non-dominated sorting genetic algorithm ii (nsga-ii) is exploited to resolve the goods location optimization problem in the pharmaceutical automated warehouses. The simulation results show that the optimization model make the goods distribution more reasonable.

关键词： Automated warehouse Goods location optimization Mathematical model nsga-ii algorithm

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