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The Performance Indices Optimization of a Symmetrical Fully Spherical Parallel Mechanism for Dimensional Synthesis

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2018年第3-4期90卷 305-321页

作者： Enferadi, Javad Nikrooz, Reza Islamic Azad Univ Dept Mech Engn Mashhad Branch Mashhad Iran

The 3(UPS)-S fully spherical parallel manipulator is the most famous fully spherical parallel robot. Therefore, dimensional synthesis of the manipulator to optimize kinematics and dynamic performance indices is very important. In this paper, we proposed a new kinematics index that is called global workspace conditioning index (GWCI). This index is a suitable criteria to compare workspace of the spherical parallel manipulators. Using this index, and other performance indices such as;Global Conditioning Index (GCI), Global Gradient Index (GGI) and Dynamic Dexterity Index (DDI), we optimize dimensions of the manipulator based on single and multi-objective optimizations. Two dimensionless design parameters are advised to obtain an optimal solution. The manipulator is optimized with regard to the joints constraint and range of motion actuators as functions of the design parameters. For this purpose, we elaborate kinematics analyses and also obtain the mass matrix of the manipulator using its kinetic energy. Next, single-objective optimizations based on genetic algorithm (GA) and Pattern Search (PS) are presented. The comparison between GA and PS in the single-objective optimization shows that the accuracy of both methods is rather equal, but in elapsed time PS is better than GA. Finally, multi-objective evolutionary algorithm based on the non-dominated sorting genetic algorithm II (NSGA-II) is adopted to find the true optimal solutions and Pareto fronts. The obtained solution will be a set of optimal geometric parameters to adjust the dynamic and the kinematic performance.

关键词： Dimensional synthesis Global workspace conditioning index Performance indices genetic algorithm Pattern search non-dominated sorting genetic algorithm

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Multi-objective optimization for scheduling multi-load automated guided vehicles with consideration of energy consumption

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2024年 161卷

作者： Huo, Xiang He, Xiaozheng Xiong, Zhongxia Wu, Xinkai Beihang Univ Sch Transportat Sci & Engn Beijing 100191 Peoples R China Beijing Robint Technol Co Ltd Xueyuan Rd Beijing 100191 Peoples R China Rensselaer Polytech Inst Dept Civil & Environm Engn Troy NY 12180 USA

The widespread implementation of modern logistics has led to the extensive use of multi-load automatic guided vehicles (m-AGVs) in automated sorting centers. This paper tackles one of the most challenging problems in this context, i.e., the scheduling of m-AGVs for express package handling. We comprehensively consider the loading and unloading delay of packages and energy consumption of m-AGVs, formulating the problem as a multi-objective mixed integer program (MO-MIP). To solve the proposed optimal scheduling problem, we apply the non-dominated sorting genetic algorithm (NSGA-II). A series of simulation experiments on three sorting centers have been further conducted to demonstrate the effectiveness and efficiency of the proposed model and solution algorithm.

关键词： Multi-load automatic guided vehicles (m-AGVs) Multi-objective mixed integer program (MO-MIP) Scheduling non-dominated sorting genetic algorithm (NSGA-II)

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Combining local search into non-dominated sorting for multi-objective line-cell conversion problem

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INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2013年第4期26卷 316-326页

作者： Yu, Yang Tang, Jiafu Sun, Wei Yin, Yong Kaku, Ikou Northeastern Univ Inst Syst Engn State Key Lab Synthet Automat Proc Ind Shenyang 110819 Peoples R China Liaoning Univ Coll Business Adm Shenyang 110136 Peoples R China Yamagata Univ Dept Econ & Business Management Yamagata 9908560 Japan Tokyo City Univ Fac Environm & Informat Studies Yokohama Kanagawa 2248551 Japan

Multi-objective decision-making is often used in line-cell conversion problem. It is the key issue of developing line-cell conversion successfully. In this article, a multi-objective optimisation model is proposed to investigate two line-cell conversion performances: the total throughput time and the total labour hours. It is proved that the model is a non-deterministic polynomial (NP)-hard problem and its Pareto-optimal front is non-convex. Owing to the properties of cell formation and cell loading in line-cell conversions, an approach of combining local search into non-dominated sorting genetic algorithm II is proposed to obtain better non-dominated solutions. Several numerical simulation experiments are performed to show the utility and performance of our approach.

关键词： line-cell conversion multi-objective optimisation local search non-dominated sorting genetic algorithm

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Application of Biogeography-based Optimization for Solving Multi-objective Economic Emission Load Dispatch Problems

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2010年第3期38卷 340-365页

作者： Bhattacharya, Aniruddha Chattopadhyay, P. K. Jadavpur Univ Dept Elect Engn Kolkata 700032 India

This article presents a biogeography-based optimization algorithm to solve complex economic emission load dispatch problems of thermal generators of power systems. Different emission substances, such as NOX, SOX, and COX, are considered for case studies. The methodology considers the power demand equality constraint and the operating limit constraint during the time of solving economic emission load dispatch problems. Biogeography deals with the geographical distribution of biological organisms. Mathematical models of biogeography describe how species migrate from one habitat to another, how species arise, and how species become extinct. Here, it will be discussed how biogeography-based optimization can be used to solve economic emission load dispatch problems. This algorithm searches the global optimum mainly through two steps: migration and mutation. To show the advantages of the proposed algorithm, this algorithm has been applied for solving multi-objective economic emission load dispatch problems in a six-generator system considering NOX emission for different loading condition;in a three-generator system with NOX and SOX emission;in a six-generator system with SOX, NOX, and COX emissions;and in a six-generator system addressing both valve-point loading and NOX emission. Compared with the other existing techniques, the current proposal is found to be better in terms of quality of the compromising and individual solution obtained.

关键词： biogeography-based optimization economic emission load dispatch particle swarm optimization non-dominated sorting genetic algorithm valve-point loading

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Add-on integration module-based proportional-integration-derivative control for higher precision electro-optical tracking system

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2021年第6期43卷 1347-1362页

作者： Duan, Qianwen Mao, Yao Zhang, Hanwen Xue, Wenchao Chinese Acad Sci Key Lab Opt Engn Beijing Peoples R China Chinese Acad Sci Inst Opt & Elect Beijing Peoples R China Chinese Acad Sci Acad Math & Syst Sci NCMIS LSC Zhongguancongdonglu Rd 55 Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

This paper concerns the improvement on proportional-integration-derivative (PID) control for the electro-optical tracking system for high-mobility targets. To achieve higher tracking precision and stronger disturbance rejection while fully utilizing the existing PID loop, the add-on integration module is proposed and seamlessly integrated into the conventional PID loop. It is proven that for any given conventional PID controller parameters, the add-on integration module based PID control can improve the ability of error attenuation at low frequency and keep the stability of resulting closed-loop system. More importantly, the feasible set of all parameters in the added module is explicitly given. Based on the feasible set, the non-dominated sorting genetic algorithm II (NSGA-II) is adopted to obtain the globally optimal controller's parameter under certain performance indices. The experiments are carried out for a typical electro-optical tracking test bed with several reference signals. It is shown that the proposed method has much smaller tracking errors than the existing PID method.

关键词： Proportional-integration-derivative control electro-optical tracking system motion control disturbance rejection non-dominated sorting genetic algorithm

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Simultaneously maximizing microalgal biomass and lipid productivities by machine learning driven modeling, global sensitivity analysis and multi-objective optimization for sustainable biodiesel production

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APPLIED ENERGY 2024年 358卷

作者： Kumar, Ravi Ranjan Sarkar, Debasis Sen, Ramkrishna Indian Inst Technol Kharagpur Dept Biotechnol Kharagpur India Indian Inst Technol Kharagpur Dept Chem Engn Kharagpur India

Simultaneous enhancement in the productivities of microalgal biomass and lipids that are inversely correlated to each other has been a long-standing challenge before the scientists engaged in algal biodiesel research and innovation. This study, develops an Artificial Neural Network (ANN) model and uses multi-objective optimization approach to determine the process parameters, namely, light intensity, CO2%, air flow rate, and C/N ratio to maximize biomass and lipid productivities of microalga, Chlorella sorokiniana, simultaneously. Experimental data based on central composite design (CCD) were used to train a feed-forward multilayer ANN with four critical parameters. The global sensitivity analysis was performed on the trained ANN model using Sobol's method to assess the relative significance of the four process variables. Since the objectives of maximizing biomass and lipid productivities conflict with each other, multi-objective optimization approach was used for deriving the optimal process parameters, experimental validation of which resulted in approximately 3 times increase in biomass productivity and 7 times increase in lipid productivity. On transesterification of the lipid, the biodiesel product with saturated to unsaturated fatty acids ratio of 48:52 conformed very well to the international standards, ASTM D6751 and EN14214, thereby making it an environment friendly green biofuel. Thus, the present study showcases the successful application of machine learning tool in analysing the global sensitivity analysis of process variables, and employ it for multi -objective optimization towards achieving maximum microalgal biomass and lipid productivities concomitantly for potentially sustainable production of biodiesel.

关键词： Algal biomass and lipid productivities Simultaneous enhancement Machine learning approaches Artificial neural network modeling Sobol's sensitivity analysis non-dominated sorting genetic algorithm Multi-objective optimization Sustainable biodiesel production

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Investigating the potential for realizing life cycle net-zero energy buildings in Europe using multi-objective optimization

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ENERGY REPORTS 2024年 12卷 5648-5670页

作者： Shadram, Farshid Mukkavaara, Jani Uppsala Univ Dept Civil & Ind Engn Div Civil Engn & Built Environm S-75105 Uppsala Sweden

In pursuit of the long-term target of achieving climate neutrality by 2050, it is crucial to strive for buildings with net-zero energy balance from a life cycle perspective. This study employs multi-objective optimization, specifically the non-dominated sorting genetic algorithm II, to explore the feasibility of achieving a life cycle net-zero energy balance for a building case in diverse European climate conditions: including Gothenburg's humid continental climate (characterized by warm to hot summers and cold, snowy winters), Frankfurt's oceanic climate (featuring short, cool summers and long, relatively mild winters), and Madrid's Mediterranean climate (marked by wet, mild winters and dry, hot summers). The study examines this feasibility across three building lifespan durations: the standard 50 years, commonly applied in life cycle analyses, as well as extended lifespans of 100 and 150 years. This examination is vital due to the impact of longer building lifespans, resulting in increased operational energy demand and higher embodied energy due to the more frequent replacements of building components and systems. The findings demonstrate the feasibility of realizing a life cycle net-zero energy building across diverse European climatic conditions and lifespan durations through the identification of optimal passive, active, and renewable measures. The results emphasize the essential role of renewable measures, such as photovoltaic (PV) panels, in effectively offsetting any surplus energy use throughout the building's life cycle, ultimately enabling the achievement of a life cycle net-zero energy building. It was observed that a minimum of 276 m2 (approximate to 63.5 kWp), 246 m2 (approximate to 56.5 kWp), and 131 m2 (approximate to 30.1 kWp) of PV panels would be required to realize a life cycle net-zero energy building in Gothenburg, Frankfurt, and Madrid, respectively. Across all locations and lifespan durations, these PV panels were integrated with optimal acti

关键词： Embodied energy Energy efficiency measures Life cycle net-zero energy building Multi-objective optimization non-dominated sorting genetic algorithm Operational energy

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A multi-attribute personalized recommendation method for manufacturing service composition with combining collaborative filtering and genetic algorithm

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JOURNAL OF MANUFACTURING SYSTEMS 2021年第PartA期58卷 348-364页

作者： Liu, Zhengchao Wang, Lei Li, Xixing Pang, Shibao Jiangxi Univ Sci & Technol Sch Mech & Elect Engn Ganzhou 341000 Peoples R China Wuhan Univ Technol Sch Mech & Elect Engn Wuhan 430070 Peoples R China Hubei Univ Technol Sch Mech Engn Wuhan 430068 Peoples R China

With the popularity of service-oriented manufacturing mode, the customer quantities of the online manufacturing service platforms are growing exponentially. To improve the user-friendliness and convenience of online platforms, the personalized service recommendation for different customer requirement is an effective means. However, since manufacturing services usually appear in the form of composite services, existing Web service-based personalized recommendation technologies are difficult to be applied effectively. Therefore, this paper proposes a novel hybrid algorithm to address the personalized recommendation for manufacturing service composition (MSC). The algorithm solves the insufficient individualization defect of MSC optimization by comprehensively considering the QoS objective attributes and customer preference attributes. First, a Clustering-based Collaborative Filtering (CCF) algorithm is proposed to quantify the customer preference attributes. Second, an improved Personalization-oriented third generation non-dominated sorting genetic algorithm (PoNSGA-III) is presented for the multi-attribute MSC optimization. Finally, the hybrid algorithm recommends the most suitable solutions for the target customer through the ranking of customer preference attributes. A detailed case study is designed to demonstrate the performance and practicability of the proposed recommendation algorithm.

关键词： Multi-attribute personalized recommendation Manufacturing service composition optimization Collaborative filtering non-dominated sorting genetic algorithm

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Combined genetic algorithm and response surface methodology-based bi-optimization of a vertical-axis wind turbine numerically simulated using CFD

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ENERGY SCIENCE & ENGINEERING 2024年第10期12卷 4532-4548页

作者： Roshani, Mahdi Pourfayaz, Fathollah Gholami, Ali Univ Tehran Coll Interdisciplinary Sci & Technol Sch Energy & Sustainable Resources Engn Tehran Iran

In this study, computational fluid dynamic (CFD) simulation of a vertical axis wind turbine (VAWT) geometry based on the Unsteady Reynolds-Averaged Navier-Stokes equations was investigated. In addition, the relationship between the geometric parameters of the VAWT and the two response variables, that is, moment and lift force, was determined using response surface methodology (RSM). Then, the non-dominated sorting genetic algorithm (NSGA-II) was used to solve the multi-objective optimization problem. The results obtained from the RSM showed that the lift force of the turbine is more sensitive to the change in the blade chord length, and the output moment of the turbine is more sensitive to the change in the rotor radius. Using the NSGA-II multi-objective optimization algorithm and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, it was determined that among the optimal values of the independent variable, the most optimal response occurs in blade chord length = 0.18 m, rotor radius = 0.4 m, blade pitch angle = -3.27 degrees and number of blades = 4. In these optimal values of the independent variables, the values of the dependent variables, which included the turbine's moment and the blades' lift force, were obtained as 9.58 N m and 57.89 N, respectively. The optimum values of moment and lift force for a vertical axis wind turbine were determined by a multi-objective optimization methodology including response surface methodology (RSM), computational fluid dynamic (CFD), non-dominated sorting genetic algorithm (NSGA-II), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Under the optimal conditions of blade chord length = 0.18 m, rotor radius = 0.4 m, blade pitch angle = -3.27 degrees, and number of blades = 4, the values of the turbine's moment and the blades' lift force were obtained as 9.58 N m and 57.89 N, respectively. image

关键词： CFD Darrieus wind turbine non-dominated sorting genetic algorithm response surface methodology TOPSIS method wind energy

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Mechanisms of characteristic parameters of plasma actuator on film cooling and turbulent transport based on multi-objective optimization

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APPLIED THERMAL ENGINEERING 2024年 240卷

作者： Sun, Jie Xie, Gongnan Northwestern Polytech Univ Sch Marine Sci & Technol Xian 710072 Peoples R China Northwestern Polytech Univ Sch Marine Sci & Technol POB 24 Xian 710072 Peoples R China

In this paper, film cooling effectiveness and pressure loss coefficient are taken as the objective functions to optimize the plasma characteristic parameters such as electrode position, spacing, length and actuation intensity for enhancing film cooling performance. Regression equations of two objective functions are accessed by the Response Surface Method, and non-dominated sorting genetic algorithm is applied for bi-objective optimization. Two sets of Pareto optimal solutions are available via the Technique for Order Preference by Similarity to an Ideal Solution decision method. Pareto optimal solutions are calculated by Detached Eddy Simulation to clarify the turbulent transport and heat transfer characteristics induced by the plasma. Wall-averaged cooling effectiveness and pressure loss coefficient without plasma power supply are 64.3 % and 3.9 % superior to that without electrode, respectively. The plasma fragments the hairpin vortex into a striped structure and induces a large scale streamwise vortex behind the bare electrode. The plasma weakens the velocity diffusion and turbulent heat transport in the ionization zone. Overlapping electrodes render the root-mean-square pulsation velocity and Reynolds shear stress of the optimal model 1 both less than those of the optimal model 2 without overlapping electrodes, and flow field disorder is decreased. Electrode position interferes with the action location of plasma on cooling jet. Actuation intensity affects the ionization intensity and has a maximum value of 8.88 to optimize the actuator performance. Compared with no plasma actuation, wall-averaged cooling effectiveness of optimal model 1 and optimal model 2 are enhanced by 30.7 % and 21.8 %, and pressure loss coefficient are declined by 7.7 % and 7.1 %, respectively.

关键词： Film cooling Plasma aerodynamic actuation non-dominated sorting genetic algorithm Response surface method Detached eddy simulation

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