scholarly journals Multiobjective Optimization Model for Profile Design of Hump Distributing Zone

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Hongliang Zhang ◽  
Jing Yang ◽  
Taoyuan Yang
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Model ◽  
Improved Genetic Algorithm ◽  
Special Equipment ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Railway Freight ◽  
Contrast Analysis ◽  
Profile Design

Railway freight trains consist of many cars heading to different destinations. Hump is the special equipment that distributes cars with different destinations to different tracks in a marshalling station. In recent years, with the development of Chinese freight car technology, the axle load has risen from 21 ton to 23 ton and will rise to 27 ton in the future. Many rolling problems appear in the hump distributing zone with the application of 23-ton axle load cars, which will be exacerbated by 27-ton axle load cars. This paper proposes a multiobjective optimization model based on the angle of the hump profile design with minimizing weighted accumulating rolling time (WART) and hump height as optimization goals and uses the improved genetic algorithm NSGA-II to determine a solution. In case study, Pareto solution set is obtained, and the contrast analysis with traditional method is made.

scholarly journals A Multiobjective Optimization Model for Continuous Allocation of Emergency Rescue Materials

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yonghong Liu ◽  
Yucheng Li ◽  
De Huang
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Model ◽  
Supply And Demand ◽  
Economic Losses ◽  
Allocation Scheme ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Emergency Relief ◽  
Rescue Work ◽  
Emergency Rescue

Emergency rescue operations play a vital role in alleviating human suffering, reducing casualties, and cutting down economic losses. One key aspect in the management of these operations is the rational allocation of emergency relief materials, where the allocation is continuous, dynamic, and concurrent. This allocation should be made not only to minimize the emergency rescue losses, but also to reduce the cost of emergency rescue work. A reasonable and effective allocation scheme for emergency relief materials can be established to adapt to the continuity, dynamics, and concurrency of material distribution. In this work, we propose a multiobjective optimization model of emergency material allocation with continuous time-varying supply and demand constraints, where the objective is to minimize the losses and the economic cost incurred by the emergency rescue operations. The constrained optimization problem is handled through sequential unconstrained minimization techniques, and the multiobjective optimization is carried out by the fast nondominated sorting genetic algorithm (NSGA-II) with an elite strategy to obtain a Pareto solution set with fairness and balance of loss and cost. The loss and cost associated with the Pareto frontier are employed to find an appropriate noninferior solution and its corresponding material allocation scheme. We verify through several simulations the model feasibility and the effectiveness of the proposed method, which can provide decision support for continuous material allocation in emergency rescue operations.

scholarly journals Multiobjective Optimization Model for Sustainable Waste Management Network Design

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Sun Olapiriyakul ◽  
Warut Pannakkong ◽  
Warith Kachapanya ◽  
Stefano Starita
Keyword(s):  
Multiobjective Optimization ◽  
Waste Management ◽  
Optimization Model ◽  
Negative Impact ◽  
Cost Effective ◽  
Management Systems ◽  
Large Share ◽  
Rapid Urbanization ◽  
Transportation Routes

Inefficient or poorly planned waste management systems are a burden to society and economy. For example, excessively long waste transportation routes can have a negative impact on a large share of the population. This is exacerbated by the rapid urbanization happening worldwide and in developing countries. Sustainability issues should be accounted for at every stage of decision making, from strategic to daily operations. In this paper, we propose a multiobjective optimization model to design a cost-effective waste management supply chain, while considering sustainability issues such as land-use and public health impacts. The model is applied to a case study in Pathum Thani (Thailand) to provide managerial insights.

scholarly journals Research on Optimization of Customized Bus Routes Based on Uncertainty Theory

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zi Sang ◽  
Bing Zhang ◽  
Yunqiang Xue ◽  
Hongzhi Guan
Keyword(s):  
Optimization Model ◽  
Uncertainty Theory ◽  
Optimization Problem ◽  
Route Planning ◽  
Route Optimization ◽  
Improved Genetic Algorithm ◽  
Optimization Scheme ◽  
Theoretical Support ◽  
Vehicle Operation

In the optimization process of the routes of customized buses, there are numerous uncertainties in the route planning and setting. In this study, the uncertainty theory is introduced into the optimization problem of a customized bus route, and an uncertain customized bus route optimization model is established, which aims at the minimizing the total mileage of vehicle operation. An improved genetic algorithm is used to solve the model, whose feasibility is verified by a case study. The results show that the optimization model based on the uncertainty theory can yield a reasonable customized bus route optimization scheme, and the total mileage reduced from 35.6 kilometers to 32.2 kilometers. This research provides the theoretical support for the optimization of customized bus routes.

Multiobjective Optimization for Dynamic Umbilical Installation Using Non-Dominated Sorting Genetic Algorithm

2011 ◽  
Author(s):  
Aijun Wang ◽  
Hezhen Yang ◽  
Huajun Li
Keyword(s):  
Genetic Algorithm ◽  
Multiobjective Optimization ◽  
Cost Effective ◽  
Optimization Strategy ◽  
Approximation Model ◽  
Dynamic Nature ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Dynamic Analyses ◽  
Optimal Deployment

This paper presents a method of multiobjective optimization based on approximation model for dynamic umbilical installation. The optimization aims to find out the most cost effective size, quantity and location of buoyancy modules for umbilical installation. Due to the highly geometrically nonlinearity and highly responsive dynamic nature in deepwater, dynamic umbilical analysis is very complex and time-consuming. Approximation Model constructed by design of experiment (DOE) sampling is utilized to solve this problem. Non-linear dynamic analyses considering environmental loadings are executed on these sample points from DOE. Non-dominated Sorting Genetic Algorithm (NSGA-II) is employed to obtain the Pareto solution set through an evolutionary optimization process. The optimization results indicate this optimization strategy with approximation model is valid, and provide the optimal deployment way of buoyancy modules.

scholarly journals An Optimal Source-Load Coordinated Restoration Method Considering Double Uncertainty

Energies ◽  
2018 ◽  
Vol 11 (3) ◽  
pp. 558 ◽  
Author(s):  
Ping Jiang ◽  
Qiwei Chen
Keyword(s):  
Optimization Model ◽  
Nsga Ii ◽  
Power System Restoration ◽  
Information Gap ◽  
Start Up ◽  
Uncertainty Optimization ◽  
System Restoration ◽  
Restoration Method ◽  
The Time Domain

The security of power system restoration is severely affected by uncertain factors, especially the start-up time of generating unit and the amount of load pick-up. Solving the optimization restoration problem is challenging since it needs to determine different priorities in which units and loads are restored with the consideration of double uncertainty. Therefore, an optimal source-load coordinated restoration method that is based on information gap decision theory (IGDT) is proposed. Firstly, the time-domain restoration characteristics of black-start unit (BSU), non-black-start unit (NBSU), and load are described with analysis of double uncertainty. On this basis, a coupled multi-objective optimization model is built with double uncertainty, in which source-load coordinated restoration is realized. Then, IGDT is adopted to convert the uncertainty optimization model to a certain one with robustness, which tolerates the most uncertainty and still meets the desired requirement. Finally, the optimization model is solved by non-dominated genetic algorithm II (NSGA-II). The effectiveness and robustness of the proposed method is further illustrated through a case study based on the IEEE 39-bus system.

Construction of plastic contact deformation maps on ceramics: a case study on aluminum nitride

1996 ◽  
Vol 54 ◽  
pp. 636-637
Author(s):  
D. L. Callahan
Keyword(s):  
Plastic Deformation ◽  
Aluminum Nitride ◽  
Mechanical Response ◽  
Three Dimensional ◽  
Bright Field Image ◽  
Perfectly Plastic ◽  
Contrast Analysis ◽  
Deformation Patterns

Modern polishing, precision machining and microindentation techniques allow the processing and mechanical characterization of ceramics at nanometric scales and within entirely plastic deformation regimes. The mechanical response of most ceramics to such highly constrained contact is not predictable from macroscopic properties and the microstructural deformation patterns have proven difficult to characterize by the application of any individual technique. In this study, TEM techniques of contrast analysis and CBED are combined with stereographic analysis to construct a three-dimensional microstructure deformation map of the surface of a perfectly plastic microindentation on macroscopically brittle aluminum nitride.The bright field image in Figure 1 shows a lg Vickers microindentation contained within a single AlN grain far from any boundaries. High densities of dislocations are evident, particularly near facet edges but are not individually resolvable. The prominent bend contours also indicate the severity of plastic deformation. Figure 2 is a selected area diffraction pattern covering the entire indentation area.

scholarly journals Analysis and optimization of the vehicle handling stability with considering suspension kinematics and compliance characteristics

2021 ◽  
Vol 13 (5) ◽  
pp. 168781402110155
Author(s):  
Jin Gao ◽  
Fuquan Wu
Keyword(s):  
Dynamic Model ◽  
Great Influence ◽  
Transient State ◽  
Transient Characteristic ◽  
Nsga Ii ◽  
Pareto Solution ◽  
Characteristic Index ◽  
Yaw Rate ◽  
Comparison Results ◽  
Force Calculation

The dynamic model of the front double wishbone suspension and the rear multi-link suspension of the vehicle are established. On the basis of detailed analysis of suspension kinematics, calculation method of wheel alignment angle and force calculation of suspension bushing, the influence mechanism of suspension bushing on the vehicle transient state is clarified, and the vehicle transient characteristic index is derived from the vehicle three-free dynamic model. The sensitivity analysis of the suspension bushing is carried out, and the bushing stiffness which has a great influence on the transient state of the vehicle is obtained. The bushing stiffness scale factor is used as the optimization variable, the vehicle transient characteristic index is used as the optimization target, and the NSGA-II optimization algorithm is used for multi-objective optimization. After optimization, one Pareto solution is selected to compare with the original vehicle, the comparison results show that the yaw rate gain, resonance frequency and delay time of yaw rate in the vehicle transient characteristic index are all improved, other optimization targets change less. In the steady-state comparison, the understeer tendency of the vehicle increases, and the roll angle of the vehicle increases but is within an acceptable range.

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