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International Conference on Smart Transportation and City Engineering

作者： Li, Ming Jiangsu Prov Planning & Design Grp Co Ltd Nanjing Peoples R China

ISBN: (数字)9781510649767

ISBN: (纸本)9781510649767;9781510649750

Traditional traffic assignment model suffers from its criteria which are travel time only, travel time and distance, travel time and reliability. All of these criteria influence route choice behavior. multi-criteria user equilibrium model considering travel time, travel time reliability and travel distance was proposed. It was proved that the week multi-criteria user equilibrium model is a generalization of user equilibrium (UE) model and travel time budget (TTB) model. multi-criteria and multi-class user equilibrium (MMUE) model was established to overcome the shortcoming of multi solution of multi-criteria user equilibrium model. Quasi-method of successive average (QMSA) was designed to solve the MMUE model. An example was used to test the speed and accuracy of proposed algorithm. And the differences of MMUE, UE and TTB model were compared. Experiments had shown that the QMSA algorithm could be quickly convergent. It is more realistic to consider the different travel value for each traveler in MMUE model.

关键词： traffic engineering user equilibrium model multi-objective programming traffic assignment

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A robust convex optimization approach to design a hierarchical organ transplant network: A case study

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EXPERT SYSTEMS WITH APPLICATIONS 2022年第0期197卷 116716-116716页

作者： Rouhani, Samira Amin, Saman Hassanzadeh Iran Univ Sci & Technol Dept Ind Engn Tehran Iran Ryerson Univ Dept Mech & Ind Engn Toronto ON Canada

Organ transplant network as one of the most complex and challenging networks among healthcare systems, requires an effective supply chain design. In this research, a novel bi-objective hierarchical location-allocation model is developed to design an organ transplant network. The goal is to simultaneously minimize the total time and costs, and maximize the geographic parity in the network under supply and demand uncertainty. Different transportation modes are considered in the developed network, and the optimum transportation mode is selected after solving the model. The augmented epsilon-constraint technique is applied to solve the multi-objective model. Furthermore, a convex robust optimization approach is developed to tackle uncertain nature of the parameters. Finally, a case study is presented and the optimal solutions of the developed models are calculated and analyzed.

关键词： Robust optimization Organ transplant network Healthcare management Facility Location multi-objective programming

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A credibility-based interval multi-objective crop area planning model for agricultural and ecological management

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AGRICULTURAL WATER MANAGEMENT 2022年第0期269卷

作者： Chen, Junxu Zhang, Chenglong Guo, Ping China Agr Univ Coll Water Resource & Civil Engn Beijing 100083 Peoples R China Natl Observ & Res Stn Oasis Agr Ecosyst Wuwei Gansu Peoples R China

This study presents a credibility-based interval multi-objective crop area planning model for agricultural and ecological management under uncertainty. The model is developed through the integrations of interval multi-objective programming and fuzzy credibility-constrained programming by considering economic and ecological benefits of the study system, and dealing with interval and fuzzy uncertainties. It focuses on crop area optimization with the interval objective function of maximizing the system benefits, maximizing the watershed area, and fractional interval objective function of maximizing the land productivity (i.e., system benefits per unit area). Additionally, the relationship between watershed area and ecological discharge is expressed as interval linear function, which is estimated by using interval regression analysis method. Then, the model is applied to a case study in Minqin County in the lower reaches of Shiyang River Basin for crop area optimization in view of the increasing shortage of water resources and the competition between agricultural and ecological water use. Optimal solutions for different scenarios can be generated based on fuzzy credibility constraints when the pre-defined credibility levels are set as 0.6, 0.7 and 0.8, 0.9, respectively. The results show that the crop area optimization model can better balance the regional agricultural and ecological benefits while ensuring grain production and promoting water saving. Moreover, a higher level of credibility corresponds to a lower system benefit but a larger watershed area. When credibility level is raised from 0.6 to 0.9, the upper bounds of system benefits are decreased from 13.87x10(8) Yuan to 13.81x10(8) Yuan whereas the watershed area is increased from 41.01 km(2) to 42.12 km(2). These various optimal results can help decision makers weigh system benefits and constraint-violation risks. Therefore, the results of the model can provide decision-making basis for the crop area optimizat

关键词： Interval multi-objective programming Credibility Ecological management Crop area planning Uncertainty

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An Improved Ant Colony Algorithm for UAV Path Planning in Uncertain Environment

An Improved Ant Colony Algorithm for UAV Path Planning in Un...

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International Joint Conference on Neural Networks (IJCNN)

作者： Rao, Yizhuo Cao, Jianjun Zeng, Zhixian Duan, Chengyuan Wei, Xiao Acad Mil Med Sci Mil Sci Informat Res Ctr Beijing Peoples R China Natl Univ Def Technol Res Inst 63 Nanjing Peoples R China

ISBN: (纸本)9780738133669

Track planning for drones has been a common problem. In order to ensure that the UAV can fly long distance in accordance with the predetermined path, it is necessary to set calibration points on the flight path to correct the sensor errors of the UAV. This problem can be abstracted into a path planning problem and solved by ant colony algorithm. Considering the uncertainty of correction failure in these calibration points. This paper presents an improved ant colony algorithm and set up the "Enhanced pheromone volatilization strategy" to ensure that the UAV could reach the destination with the greatest possibility in this uncertain situation. We verify our algorithm on public data sets**. On data set 1, our algorithm has a 100% probability of reaching the destination, while the traditional ant colony algorithm has only a 61% probability of reaching the destination. On data set 2, our algorithm has a 56% probability of reaching the destination, while the traditional ant colony algorithm cannot find a path can reach the destination. The algorithm code*** in this paper is simple to implement, strong robustness, and can be extended to other scenarios.

关键词： ant colony algorithm path planning unmanned aerial vehicle optimization under uncertainty multi-objective programming

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Economic-Environment-Energy (3E) objective-driven integrated municipal waste management under deep complexities - A novel multi-objective approach

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SUSTAINABLE CITIES AND SOCIETY 2022年第0期87卷

作者： Liang, Xiaolin Ji, Ling Xie, Yulei Huang, Guohe Beijing Univ Technol Sch Econ & Management Beijing 100124 Peoples R China Guangdong Univ Technol Inst Environm & Ecol Engn Guangzhou 510006 Guangdong Peoples R China Univ Regina Inst Energy Environm & Sustainable Communities Regina SK S4S 0A2 Canada

Waste-to-energy technologies compatible with recycling are promising solutions for sustainable municipal waste management from both economic and environmental perspectives. This study focuses on the economic -environment-energy (3E) objective-driven integrated waste management optimization problems under deep complexities. A novel multi-objective programming model is developed to assist the optimal decision-making with the consideration of system profit, greenhouse gas emission, and energy recovery simultaneously. Be-sides, it advances existing optimization methods by incorporating interval-valued fuzzy numbers to tackle the ambiguity and the essential fuzziness in experts' judgment. It was verified by a case study from an urban district of Beijing, China. The optimum waste treatment facility planning and waste stream allocation strategies with multi-objective tradeoffs were obtained to support decision-making considering different preferences of impor-tance ranking. In general, incineration and anaerobic digestion would be the main technologies for waste disposal in the study area. Recycling would be greatly encouraged when pursuing more economic profits and greenhouse gas emission reduction. With withdrawing the subsidy in the future, the investment in anaerobic digestion would become less attractive. Meanwhile, the landfill with gas recovery would even become economically infeasible if there is no further reduction in cost. In addition, waste source separation is also a crucial factor for successful integrated waste management. It is suggested that a proper government subsidy and public participation in waste source separation would guarantee the sustainable development of the integrated waste management system.

关键词： Waste-to-energy Waste management Interval-valued fuzzy parameters multi-objective programming

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Optimal configuration of low impact development practices for the management of urban runoff pollution under uncertainty

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022年 320卷 115821页

作者： Rong, Qiangqiang Liu, Qiming Xu, Chao Yue, Wencong Su, Meirong Dongguan Univ Technol Res Ctr Ecoenvironm Engn Dongguan 523808 Peoples R China

The urbanization process has seen an accelerated increase in recent decades, leading to urban runoff pollution becoming more prominent. However, uncertainty of the pollution output and complexity of management systems have made controlling urban runoff pollution challenging. Therefore, it is necessary to propose advanced modeling methods for these challenges. This research presents an integrated urban runoff pollution management (IURPM) model for optimal configuration of low impact development (LID) practices under multiple uncertainties. The IURPM model combines the hybrid land-use prediction and improved pollution estimation models with interval parameter, stochastic parameter, and multi-objective programming. The proposed IURPM model can not only predict the output characteristics, but also provide optimal configuration schemes for the LID practices in the management of urban runoff pollution under multiple scenarios. In addition, uncertainties expressed as discrete intervals and probability density function in the management systems can be effectively addressed. A case study of the IURPM model was conducted in Dongguan City, South China. Results show that considerable amounts of urban runoff pollutants would export from Dongguan City by 2025. The export loads and pollution output flux per unit area would have significant spatial heterogeneity. The results further indicate that population size, gross domestic product, and regional area size are expected to play important roles in the pollution export, while impervious surface coverage and population density would likely have great influences on the output flux of urban runoff pollution. Based on the model findings, multiple LID practices should be adopted in Dongguan City to reduce the urban runoff pollution loads. Using the IURPM model, multiple LID implementation schemes can be obtained under different pollution reduction scenarios and significance levels, that can provide decision-making support for urban wate

关键词： Low impact development Urban runoff pollution Land use prediction multi-objective programming Interval stochastic programming

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A general inverse DEA model for non-radial DEA

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COMPUTERS & INDUSTRIAL ENGINEERING 2020年 142卷 106368-106368页

作者： Zhang, GuoJun Cui, JinChuan Chinese Acad Sci Acad Math & Syst Sci Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Math Sci Beijing 100049 Peoples R China

Traditional inverse DEA models could be called inverse radial DEA because they are based on radial efficiency measures. Due to the neglect of slacks in evaluating the efficiency score, inverse radial DEA may mislead decision-making in some cases where slacks play important roles. In this paper, we proposed an integrated framework of inverse DEA called inverse non-radial DEA since it is based on non-radial DEA by multi-objective programming, which covers existing inverse DEA models. To further illustrate the inverse non-radial DEA, we construct the concrete mathematical formula of inverse SBM and some properties. In contrast to the radial approach, inverse non-radial DEA can overcome the error caused by ignoring slacks and provides more valuable information about inputs and outputs for decision-making by considering slacks. Although inverse non-radial DEA models are usually non-linear, we can convert it into a one-dimensional search problem about efficiency score, which can be solved by many existing efficient algorithms. A practical example is provided to demonstrate the advantages of inverse non-radial DEA models over inverse radial DEA models.

关键词： Inverse DEA Non-radial DEA SBM multi-objective programming

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Designing an integrated pharmaceutical relief chain network under demand uncertainty

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2020年 136卷 101867-000页

作者： Akbarpour, Mina Torabi, S. Ali Ghavamifar, Ali Univ Tehran Sch Ind Engn Coll Engn Tehran Iran

This paper addresses an integrated relief network design problem for pharmaceutical items. The proposed bi-objective model accounts for perishability of pharmaceutical items, mobility of relief facilities, and benefits from a cooperative coverage mechanism in designing the network. A min-max robust model is developed to tackle the demand uncertainty. Several numerical experiments are conducted to explore the performance of the robust model. Also, by conducting a real case study, useful managerial insights are derived through performing several sensitivity analyses. The numerical results reveal that using the min-max robust model enhances the pharmaceutical relief network's effectiveness and efficiency considerably.

关键词： Humanitarian logistics Pharmaceutical relief items Perishability multi-objective programming Robust optimization

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Designing a green meat supply chain network: A multi-objective approach

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2020年 219卷 312-327页

作者： Mohebalizadehgashti, Fatemeh Zolfagharinia, Hossein Amin, Saman Hassanzadeh Ryerson Univ Dept Mech & Ind Engn Toronto ON Canada Ryerson Univ Ted Rogers Sch Management Toronto ON Canada

Traditional logistics management has not focused on environmental concerns when designing and optimizing food supply chain networks. However, the protection of the environment is one of the main factors that should be considered based on environmental protection regulations of countries. In this paper, environmental concerns are considered in formulating a mathematical model to design and configure a multi-period, multi-product, multi-echelon green meat supply chain network. We develop a multi-objective mixed-integer linear programming formulation to optimize three objectives simultaneously: minimization of the total cost, minimization of the total CO2 emissions released from transportation, and maximization of the total capacity utilization of facilities. To demonstrate the efficiency of the proposed optimization model, we design a green meat supply chain network for Southern Ontario, Canada. A solution approach based on augmented epsilon-constraint method is employed to solve the proposed model. As a result, a set of Pareto-optimal solutions is obtained. The set of Pareto-optimal solutions gives decision-makers the opportunity to make a trade-off between economic, environmental, and capacity utilization objectives. Our example shows that it is possible to keep emissions reasonably low without incurring high total costs. Finally, the impacts of uncertainty on the proposed model are investigated using several decision trees. Optimization of a food supply chain, particularly a meat supply chain, based on multiple objectives under uncertainty using decision trees is a new approach in the literature.

关键词： Meat supply chain Decision tree multi-objective programming Mixed-integer linear programming Augmented epsilon-constraint

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multi-objective Adaptive Robust Voltage/VAR Control for High-PV Penetrated Distribution Networks

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IEEE TRANSACTIONS ON SMART GRID 2020年第6期11卷 5288-5300页

作者： Zhang, Cuo Xu, Yan Dong, Zhao Yang Zhang, Rui Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

In active distribution networks, high penetration of distributed photovoltaic power generation may cause voltage fluctuation and violation issues. To conquer the challenges, this paper firstly proposes a load-weighted voltage deviation index (LVDI) to quantify network voltage deviation. Secondly, this paper proposes a multi-objective adaptive voltage/VAR control (VVC) framework which coordinates multiple devices in multiple timescales to minimize voltage deviation and power loss simultaneously. Then, a multi-objective adaptive robust optimization method is proposed to obtain robust Pareto solutions under uncertainties. Accordingly, solution algorithms based on different multi-objective programming algorithms and a column-and-constraint generation algorithm are developed and systematically compared. The proposed method is verified through comprehensive tests on the IEEE 123-bus system and simulation results demonstrate high effectiveness of the LVDI, high efficiency of the solution algorithms and full operating robustness of the proposed VVC method against any uncertainty realization.

关键词： Inverters Uncertainty Reactive power Voltage control Power generation Optimization methods Active distribution networks multi-objective programming photovoltaic generation adaptive robust optimization voltage VAR control uncertainties

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