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 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 Research on the Allocation of 3D Printing Emergency Supplies in Public Health Emergencies

2021 ◽  
Vol 9 ◽  
Author(s):  
Jianjia He ◽  
Gang Liu ◽  
Thi Hoai Thuong Mai ◽  
Ting Ting Li
Keyword(s):  
Public Health ◽  
3D Printing ◽  
Optimization Model ◽  
Supply And Demand ◽  
Algorithm Analysis ◽  
Multi Objective Optimization ◽  
Matching Problem ◽  
Nsga Ii ◽  
Multi Objective ◽  
Public Health Emergencies

Significant public health emergencies greatly impact the global supply chain system of production and cause severe shortages in personal protective and medical emergency supplies. Thus, rapid manufacturing, scattered distribution, high design degrees of freedom, and the advantages of the low threshold of 3D printing can play important roles in the production of emergency supplies. In order to better realize the efficient distribution of 3D printing emergency supplies, this paper studies the relationship between supply and demand of 3D printing equipment and emergency supplies produced by 3D printing technology after public health emergencies. First, we fully consider the heterogeneity of user orders, 3D printing equipment resources, and the characteristics of diverse production objectives in the context of the emergent public health environment. The multi-objective optimization model for the production of 3D printing emergency supplies, which was evaluated by multiple manufacturers and in multiple disaster sites, can maximize time and cost benefits of the 3D printing of emergency supplies. Then, an improved non-dominated sorting genetic algorithm (NSGA-II) to solve the multi-objective optimization model is developed and compared with the traditional NSGA-II algorithm analysis. It contains more than one solution in the Pareto optimal solution set. Finally, the effectiveness of 3D printing is verified by numerical simulation, and it is found that it can solve the matching problem of supply and demand of 3D printing emergency supplies in public health emergencies.

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.

A sustainable urban water management model under uncertainty: a case study

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maryam Shabani ◽  
Naser Shams Gharneh ◽  
Seyed Taghi Akhavan Niaki
Keyword(s):  
Water Management ◽  
Sustainable Development ◽  
Multiobjective Optimization ◽  
Optimization Model ◽  
Social Issues ◽  
Supply And Demand ◽  
Demand Management ◽  
Scenario Tree ◽  
Urban Water ◽  
Content Type

PurposeTackling the challenges of water scarcity requires comprehensive management according to financial, environmental and social issues. This paper aims to develop a planning approach for systematic decision-making and pay attention to uncertainties in water demand management and supply investment.Design/methodology/approachThis study presents a multiobjective optimization model to manage water resources based on the balance of supply and demand. The objectives of the model include economic, social and environmental (sustainable development) factors. The model achieves an optimal urban water portfolio by using a scenario tree.FindingsThe mathematical goal programming (GP) in a multiobjective optimization model is applied and solved by the branch and bound method. The results indicate the selected supply augmentation and demand management options in each stage for 20 years according to the dry, normal and wetness year scenarios.Practical implicationsThis model is based on a real-world case and has been implemented in the city of Karaj. It can be applied for water management of other cities concerning sustainable development as well.Originality/valueThis paper innovates by considering the sustainable development criteria that are defined using three objective functions, including economic, social and environmental factors. The balance of supply and demand concerning uncertainty has not been investigated in any urban water portfolios. The standardized precipitation evapotranspiration index (SPEI) is incorporated to generate different scenarios. To the best of the authors’ knowledge, this approach is used for the first time.

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.

scholarly journals Multiobjective Optimization Model of Production Planning in Cloud Manufacturing Based on TOPSIS Method with Combined Weights

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Zhiru Li ◽  
Wei Xu ◽  
Huibin Shi ◽  
Qingshan Zhang ◽  
Fengyi He
Keyword(s):  
Multiobjective Optimization ◽  
Production Planning ◽  
Mass Customization ◽  
Evaluation Model ◽  
Cloud Manufacturing ◽  
Production Plan ◽  
Topsis Method ◽  
Nsga Ii ◽  
Optimal Production ◽  
Planning Scheme

Combined with the research of mass customization and cloud manufacturing mode, this paper discussed the production planning of mass customization enterprises in the context of cloud manufacturing in detail, analyzed the attribute index of manufacturing resource combination, and given a system considering the characteristics of batch production in mass customization and the decentralization of manufacturing resources in cloud manufacturing environment. Then, a multiobjective optimization model has been constructed according to the product delivery date, product cost, and product quality that customers care most about. The Pareto solution set of production plan has been obtained by using NSGA-II algorithm. This paper established a six-tier attribute index system evaluation model for the optimization of production planning scheme set of mass customization enterprises in cloud manufacturing environment. The weight coefficients of attribute indexes were calculated by combining subjective and objective weights with analytic hierarchy process (AHP) and entropy weight method. Finally, the combined weights calculated were applied to the improved TOPSIS method, and the optimal production planning scheme has been obtained by ranking. This paper validated the effectiveness and feasibility of the multiobjective model and NSGA-II algorithm by the example of company A. The Pareto effective solution has been obtained by solving the model. Then the production plan set has been sorted synthetically according to the comprehensive evaluation model, and the optimal production plan has been obtained.

Tuning of Power System Stabilizers using Multiobjective Optimization NSGA II

2015 ◽  
Vol 13 (8) ◽  
pp. 2653-2660 ◽  
Author(s):  
Humberto Verdejo ◽  
Diego Gonzalez ◽  
Jose Delpiano ◽  
Cristhian Becker
Keyword(s):  
Multiobjective Optimization ◽  
Power System ◽  
Power System Stabilizers ◽  
Nsga Ii

A fuzzy multi-objective programming optimization model for emergency resource dispatching under equitable distribution principle

2021 ◽  
pp. 1-10
Author(s):  
Zhaoping Tang ◽  
Wenda Li ◽  
Shijun Yu ◽  
Jianping Sun
Keyword(s):  
Optimization Model ◽  
Programming Model ◽  
Ideal Point ◽  
Optimal Solution ◽  
Multi Objective ◽  
Emergency Rescue ◽  
Satisfaction Degree ◽  
Multi Objective Programming ◽  
Parameter Interval ◽  
Objective Programming

In the initial stage of emergency rescue for major railway emergencies, there may be insufficient emergency resources. In order to ensure that all the emergency demand points can be effectively and fairly rescued, considering the fuzzy properties of the parameters, such as the resource demand quantity, the dispatching time and the satisfaction degree, the railway emergency resources dispatching optimization model is studied, with multi- demand point, multi-depot, and multi-resource. Based on railway rescue features, it was proposed that the couple number of relief point - emergency point is the key to affect railway rescue cost and efficiency. Under the premise of the maximum satisfaction degree of quantity demanded at all emergency points, a multi-objective programming model is established by maximizing the satisfaction degree of dispatching time and the satisfaction degree of the couple number of relief point - emergency point. Combined with the ideal point method, a restrictive parameter interval method for optimal solution was designed, which can realize the quick seek of Pareto optimal solution. Furthermore, an example is given to verify the feasibility and effectiveness of the method.

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