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7th IEEE International Conference on Computer Science and Network Technology (ICCSNT)

作者： Yao, Jiachen Ning, Liang Jing, Chen Cao, Cui Zhou, Enzhe Zhang, Lun Wang, Lei State Grid Jibei Elect Power Co Ltd Chengde Power Supply Co Chengde 067000 Peoples R China State Grid Jibei Elect Power Co Ltd Tangshan Power Supply Co Tangshan 063000 Peoples R China North China Elect Power Univ Dept Automat Baoding 071000 Peoples R China

ISBN: (纸本)9781728132990

Distributed power access has a significant impact on economy and security of incremental distribution network. In this paper, economy and security are taken as the optimization goal, the constraints such as power balance and voltage deviation are constructed, and the multi-objective programming model of distributed power supply access capacity is established considering the different output scenarios of distributed power supply, and the Pareto optimal solution set is obtained by using non-dominant sequencing genetic algorithm. The validity of the proposed method is verified based on the analysis of the IEEE33 node model.

关键词： incremental power distribution network distributed power supply multi-objective programming non-dominant sequencing genetic algorithm

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Integrated linguistic entropy weight method and multi-objective programming model for supplier selection and order allocation in a circular economy: A case study

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JOURNAL OF CLEANER PRODUCTION 2020年 277卷 122597-122597页

作者： Feng, Jianghong Gong, Zongrong Jinan Univ Sch Management 601 Huangpu Ave West Guangzhou 510632 Peoples R China Guangzhou Med Univ Guangzhou Women & Childrens Med Ctr Guangzhou Peoples R China

Green supply chain management is one of the most important strategies to enhance the competitiveness of modern enterprises. Traditional supplier selection methods seldom consider the entire supply chain. Therefore, this paper proposes an integrated model combining the linguistic entropy weight method (LEWM) with multi-objective programming for supplier selection and order allocation in a circular economy. First, a comprehensive system of green supplier evaluation criteria is established, with each criterion clearly defined. Second, the LEWM is used to select qualified green suppliers, whose rankings are calculated. The proposed LEWM can not only select qualified green suppliers but also analyze each supplier's performance on each evaluation criterion;it can also provide improvement suggestions for suppliers. Third, based on the characteristics of current global supply chains in the automobile manufacturing industry, the order allocation model is established. The order allocation model constructed in this paper has three objectives: total cost minimization, carbon emission minimization, and procurement value maximization. The weighted maximum and minimum operator method is used to solve the model. Finally, the paper introduces how to use the proposed two-phase model to solve the problem of green supplier selection and order allocation, and conducts sensitivity analysis on the model results. The results show that the proposed framework can effectively resolve green supplier selection and order allocation for an automobile manufacture, and verify the scientific validity of the proposed method. This study could help to improve the relationship between companies and potential suppliers, and to improve green product development capabilities and supply chain management quality, thereby enhancing companies' market competitiveness. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Linguistic entropy weight method Supplier evaluation Green supply chain Order allocation multi-objective programming

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Solving multi-objective multilevel programming problems using two-phase Intuitionistic Fuzzy Goal programming method

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JOURNAL OF COMPUTATIONAL SCIENCE 2022年第0期63卷

作者： Mollalign, Demmelash Mushi, Allen Guta, Berhanu Addis Ababa Univ Dept Appl Math Addis Ababa Ethiopia Univ Dares Salaam Dept Math Dar Es Salaam Tanzania

This paper presents a two-phase intuitionistic fuzzy goal programming (two-phase IFGP) algorithm to solve multi-objective multilevel programming (MO-MLP) problems. The coefficient of each objective and constraint function is assumed to be triangular intuitionistic fuzzy parameters and the crisp MO-MLP problems are obtained using the accuracy function method. To avoid decision lock, the top levels set tolerance limits for decision variables to control the lower levels. The problem is modeled in the intuitionistic fuzzy environment using membership and non-membership functions for each objective function at all levels and decision variables controlled by the top levels. Then, we proposed an IFGP algorithm to achieve the highest degree of each membership and non-membership goal by minimizing unwanted deviational variables and generating compensatory solutions for all decision-makers at all levels. Moreover, in the proposed approach, two-phase IFGP is modeled to yield a compromise solution that satisfies both the MN-Pareto optimal solution and the Pareto optimal solution at each level. Also, verification of the proposed method is discussed with numerical examples.

关键词： multi-objective programming multilevel programming Intuitionistic fuzzy goal programming Intuitionistic fuzzy decision set Two-phase model

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multi-objective programming for Distributed Power Access Incremental Distribution Network

Multi-objective Programming for Distributed Power Access Inc...

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作者： Jiachen Yao Liang Ning Chen Jing Cui Cao Enzhe Zhou Lun Zhang Lei Wang Chengde Power Supply Company State Grid Jibei Electric Power Co. Ltd. Tangshan Power Supply Company State Grid Jibei Electric Power Co. Ltd. Department of Automation North China Electric Power University

关键词： incremental power distribution network distributed power supply multi-objective programming non-dominant sequencing genetic algorithm

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Development of the novelty order allocation model based on supplier's willingness – Combination of a Bayesian network and a stochastic multi-objective linear programming 22

Development of the novelty order allocation model based on s...

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Proceedings of the 2022 4th International Conference on E-Business and E-Commerce Engineering

作者： Qiu-Rui He Ping-Kuo Chen Shantou University China Great Bay University China

ISBN: (纸本)9798400700071

The aim of this study is to develop a novelty order allocation through combination of a Bayesian network and a stochastic multi-objective linear programming model to help manufacturers with order allocation decisions under the uncertainty of supplier's willingness to cooperate. In this paper, we deal with the uncertainty of the willingness to cooperate through several phases. The first phase presents the determination of the factors influencing willingness to cooperate. Then Bayesian network theory is used to deal with the uncertainty of willingness to cooperate and transformation into scenarios. Finally, a stochastic multi-objective linear programming model is developed, and the weighted-sum method is utilized to solve the model. The results demonstrate the feasibility of the approaches. The order allocation model based on supplier's willingness to cooperate proposed in this paper expands the research field and reduces the carbon emission management risk of manufacturers due to the change of supplier's willingness to cooperate.

关键词： Bayesian network Order allocation multi-objective programming willingness to cooperate

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multi objective programming problem in the hesitant fuzzy environment

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APPLIED INTELLIGENCE 2020年第10期50卷 2991-3006页

作者： Rouhbakhsh, F. F. Ranjbar, M. Effati, S. Hassanpour, H. Univ Birjand Fac Math Sci & Stat Birjand Iran Ferdowsi Univ Mashhad Dept Appl Math Mashhad Razavi Khorasan Iran Ferdowsi Univ Mashhad Ctr Excellence Soft Comp & Intelligent Informat P Mashhad Razavi Khorasan Iran

In this paper, we introduce a hesitant fuzzy multi-objective programming problem, in which the evaluation information provided by the decision makers is expressed in a hesitant fuzzy environment. For this purpose a new solution concept, namely hesitant fuzzy Pareto optimal solution to the problem is introduced, and two methods are proposed to obtain it. Then it is shown that the optimal solutions of these methods are the hesitant fuzzy Pareto optimal solutions. Finally, these methods are implemented on some illustrative examples and comparative analysis of our methodology is taken with other extensions of fuzzy sets.

关键词： multi-objective programming Hesitant fuzzy sets Hesitant fuzzy Pareto optimal solution

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Using a multi-objective programming model to validate feasibility of an underground freight transportation system for the Yangshan port in Shanghai

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TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY 2018年 81卷 463-471页

作者： Chen, Yicun Guo, Dongjun Chen, Zhilong Fan, Yiqun Li, Xiao Army Engn Univ PLA Res Ctr Underground Space Nanjing 210007 Jiangsu Peoples R China Shanghai Municipal Engn Design Inst Grp Co Shanghai 200092 Peoples R China

Preventing environmental deterioration and alleviating traffic congestion are becoming urgent problems in urban and transportation planning. Alleviating the pressure from increasing freight transportation traffic via low-emission and innovative transportation methods can reduce problems such as transportation network capacity limits and environmental pollution and contribute to the development of resource-efficient and sustainable cities in the future. Underground freight transportation systems (UFTSs) can improve service quality and transportation efficiency in urban logistics and alleviate traffic congestion and associated problems such as energy consumption and air pollution. Previous studies on urban UFTSs have focused mostly on technical feasibility and policy requirements. Studies providing a quantitative analysis of the effects of introducing a UFTS on an existing transportation network are scarce. In this study, the main goal is to create a quantitative method to analyze the effects of introducing a UFTS on the performance of a transportation network. Thus, a multi-objective programming model of an integrated aboveground-underground transportation network that considers transportation cost, time, and emissions is created. The Yangshan port in Shanghai, China is used as an example to assess whether a UFTS can significantly reduce the cost, time, distance and emissions of the aboveground freight container transportation. The weights on three objective functions are varied to analyze their effects on the solution. These results provide a reference for optimizing freight distribution plans when a UFTS is constructed and for implementing integrated aboveground-underground transportation systems in the future.

关键词： Underground freight transportation system Integrated network multi-objective programming

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Sustainable fuel portfolio optimization: Integrated fuzzy multi-objective programming and multi-criteria decision making

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JOURNAL OF CLEANER PRODUCTION 2018年 176卷 304-319页

作者： Sehatpour, Mohammad-Hadi Kazemi, Aliyeh Univ Tehran Fac Management Dept Ind Management Tehran Iran

The chronic illness of transportation sector is its excessive dependence on petroleum products that necessitates immediate actions to mitigate negative externalities. Developing an environmentally benign, economically feasible, and socially acceptable fuel portfolio can generally, improve the sustainability of future transportation systems. This study aims to predict an optimal fuel portfolio based on different concerns for light-duty vehicles of Iran in the light of alternative fuels until 2025. Six potential fossil and renewable fuels including gasoline, diesel, compressed natural gas (CNG), liquid petroleum gas (LPG), a mixture of 85% ethanol and 15% gasoline (E85) and biodiesel, and one gasoline-electric hybrid technology competed through an integrated fuzzy multi-objective programming. Seven goals with environmental, cost, social and policy nature, as well as systematic constraints and fuel priority (obtained by the application of a multi-criteria decision making (MCDM) method) had to be met in the model. The solution of the model along with the sensitivity analysis of weights and aspiration levels indicated that with an acceptable possibility of achieving the goals, CNG had the greatest share in the optimal fuel portfolio followed by gasoline, LPG and diesel. Through the intended horizon, the fossil fuels' share has declined such that 13.5% of the optimal portfolio was replaced by hybrid technology, biodiesel and E85 in 2025, and more importantly, carbon dioxide emission and fuel cost could be mitigated by 11% and 18%, respectively in the same year. Two scenarios focusing on environmental and cost goals were defined through assigning 70% and 80% of the weights to the related goals, respectively;the results revealed that the main characteristics of the optimal portfolio were stable. Likewise, the analysis of the aspiration and tolerance levels of the goals proved the stability of the model and revealed that these parameters play a sensitive role in the model an

关键词： Fuel portfolio optimization Transportation alternative fuel multi-objective programming Light-duty vehicle Biofuel

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An interval multi-objective programming model for irrigation water allocation under uncertainty

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AGRICULTURAL WATER MANAGEMENT 2018年 196卷 24-36页

作者： Li, Mo Fu, Qiang Singh, Vijay P. Liu, Dong Northeast Agr Univ Sch Water Conservancy & Civil Engn Harbin 150030 Heilongjiang Peoples R China Northeast Agr Univ Key Lab Efficient Utilizat Agr Water Resources Minist Agr Harbin 150030 Heilongjiang Peoples R China Texas A&M Univ Dept Biol & Agr Engn 201 Scoates Hall2117 TAMU College Stn TX 77843 USA Texas A&M Univ Zachry Dept Civil Engn 201 Scoates Hall2117 TAMU College Stn TX 77843 USA

An interval linear multi-objective programming (ILMP) model for irrigation water allocation was developed, considering conflicting objectives and uncertainties. Based on the generation of interval numbers through statistical simulation, the ILMP model was solved using a fuzzy programming method. The model balances contradictions among economic net benefit, crop yield and water-saving in irrigation systems incorporating uncertainties in both objective functions and constraints that are based on the conjunctive use of surface water and groundwater. The model was applied to Hulan River irrigation district, northeast China. Tradeoffs between various crops in different subareas under different frequencies were analyzed, and scenarios with different objectives were considered to evaluate the changing trend of irrigation water *** indicated that the ILMP model provided effective linkages between revenue/output promotion and water saving, and offers insights into tradeoffs for irrigation water management under uncertainty. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Irrigation water allocation multi-objective programming Interval number Bootstrap Scenario analysis

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Lexicographic optimal solution of the multi-objective programming problem subject to max-product fuzzy relation inequalities

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FUZZY SETS AND SYSTEMS 2018年 341卷 92-112页

作者： Yang, Xiao-Peng Yuan, De-Hui Cao, Bing-Yuan Hanshan Normal Univ Dept Math & Stat Chaozhou 521041 Guangdong Peoples R China Guangzhou Univ Sch Math & Informat Sci Guangzhou 510006 Guangdong Peoples R China Guangzhou Vocat Coll Sci & Technol Guangzhou 510550 Guangdong Peoples R China

It is shown in this paper that the emission base stations in wireless communication can be reduced into a system of fuzzy relation inequalities with max-product composition. For optimal management in such system, we introduce the fuzzy relation multi-objective programming. Concept of feasible index set (FIS) is defined, based on which a novel algorithm, named FIS algorithm, is developed to find the unique lexicographic optimal solution of the proposed problem with polynomial computational complexity. Applying this method, we needn't to find out all the minimal solutions of the constraint. A numerical application example is provided to illustrate the feasibility and efficiency of the FIS algorithm. (c) Elsevier B.V. All rights reserved.

关键词： Fuzzy relation inequality multi-objective programming Lexicographic order Feasible index set Fuzzy relation equation Wireless communication

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